Identity Security Is Now the #1 Attack Vector — and Most Organizations Are Not Architected for It

Posted on December 8, 2025 by Brent Huston

How identity became the new perimeter

In 2025, identity is no longer simply a control at the edge of your network — it is the perimeter. As organizations adopt SaaS‑first strategies, hybrid work, remote access, and cloud identity federation, the traditional notion of network perimeter has collapsed. What remains is the identity layer — and attackers know it.

Today’s breaches often don’t involve malware, brute‑force password cracking, or noisy exploits. Instead, adversaries leverage stolen tokens, hijacked sessions, and compromised identity‑provider (IdP) infrastructure — all while appearing as legitimate users.

SyntheticID

That shift makes identity security not just another checkbox — but the foundation of enterprise defense.

Failure points of modern identity stacks

Even organizations that have deployed defenses like multi‑factor authentication (MFA), single sign‑on (SSO), and conditional access policies often remain vulnerable. Why? Because many identity architectures are:

Overly permissive — long‑lived tokens, excessive scopes, and flat permissioning.
Fragmented — identity data is scattered across IdPs, directories, cloud apps, and shadow IT.
Blind to session risk — session tokens are often unmonitored, allowing token theft and session hijacking to go unnoticed.
Incompatible with modern infrastructure — legacy IAMs often can’t handle dynamic, cloud-native, or hybrid environments.

In short: you can check off MFA, SSO, and PAM, and still be wide open to identity‑based compromise.

Token‑based attack: A walkthrough

Consider this realistic scenario:

An employee logs in using SSO. The browser receives a token (OAuth or session cookie).
A phishing attack — or adversary-in-the-middle (AiTM) — captures that token after the user completes MFA.
The attacker imports the token into their browser and now impersonates the user — bypassing MFA.
The attacker explores internal SaaS tools, installs backdoor OAuth apps, and escalates privileges — all without tripping alarms.

A single stolen token can unlock everything.

Building identity security from first principles

The modern identity stack must be redesigned around the realities of today’s attacks:

Identity is the perimeter — access should flow through hardened, monitored, and policy-enforced IdPs.
Session analytics is a must — don’t just authenticate at login. Monitor behavior continuously throughout the session.
Token lifecycle control — enforce short token lifetimes, minimize scopes, and revoke unused sessions immediately.
Unify the view — consolidate visibility across all human and machine identities, across SaaS and cloud.

How to secure identity for SaaS-first orgs

For SaaS-heavy and hybrid-cloud organizations, these practices are key:

Use a secure, enterprise-grade IdP
Implement phishing-resistant MFA (e.g., hardware keys, passkeys)
Enforce context-aware access policies
Monitor and analyze every identity session in real time
Treat machine identities as equal in risk and value to human users

Blueprint: continuous identity hygiene

Use systems thinking to model identity as an interconnected ecosystem:

Pareto principle — 20% of misconfigurations lead to 80% of breaches.
Inversion — map how you would attack your identity infrastructure.
Compounding — small permissions or weak tokens can escalate rapidly.

Core practices:

Short-lived tokens and ephemeral access
Just-in-time and least privilege permissions
Session monitoring and token revocation pipelines
OAuth and SSO app inventory and control
Unified identity visibility across environments

30‑Day Identity Rationalization Action Plan

Day	Action
1–3	Inventory all identities — human, machine, and service.
4–7	Harden your IdP; audit key management.
8–14	Enforce phishing-resistant MFA organization-wide.
15–18	Apply risk-based access policies.
19–22	Revoke stale or long-lived tokens.
23–26	Deploy session monitoring and anomaly detection.
27–30	Audit and rationalize privileges and unused accounts.

More Information

If you’re unsure where to start, ask these questions:

How many active OAuth grants are in our environment?
Are we monitoring session behavior after login?
When was the last identity privilege audit performed?
Can we detect token theft in real time?

If any of those are difficult to answer — you’re not alone. Most organizations aren’t architected to handle identity as the new perimeter. But the gap between today’s risks and tomorrow’s solutions is closing fast — and the time to address it is now.

Help from MicroSolved, Inc.

At MicroSolved, Inc., we’ve helped organizations evolve their identity security models for more than 30 years. Our experts can:

Audit your current identity architecture and token hygiene
Map identity-related escalation paths
Deploy behavioral identity monitoring and continuous session analytics
Coach your team on modern IAM design principles
Build a 90-day roadmap for secure, unified identity operations

Let’s work together to harden identity before it becomes your organization’s softest target. Contact us at microsolved.com to start your identity security assessment.

References

BankInfoSecurity – “Identity Under Siege: Enterprises Are Feeling It”
SecurityReviewMag – “Identity Security in 2025”
CyberArk – “Lurking Threats in Post-Authentication Sessions”
Kaseya – “What Is Token Theft?”
CrowdStrike – “Identity Attacks in the Wild”
Wing Security – “How to Minimize Identity-Based Attacks in SaaS”
SentinelOne – “Identity Provider Security”
Thales Group – “What Is Identity Security?”
System4u – “Identity Security in 2025: What’s Evolving?”
DoControl – “How to Stop Compromised Account Attacks in SaaS”

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

Non-Human Identities & Agentic Risk:

Posted on December 1, 2025 by Brent Huston

The Security Implications of Autonomous AI Agents in the Enterprise

Over the last year, we’ve watched autonomous AI agents — not the chatbots everyone experimented with in 2023, but actual agentic systems capable of chaining tasks, managing workflows, and making decisions without a human in the loop — move from experimental toys into enterprise production. Quietly, and often without much governance, they’re being wired into pipelines, automation stacks, customer-facing systems, and even security operations.

And we’re treating them like they’re just another tool.

They’re not.

These systems represent a new class of non-human identity: entities that act with intent, hold credentials, make requests, trigger processes, and influence outcomes in ways we previously only associated with humans or tightly-scoped service accounts. But unlike a cron job or a daemon, today’s AI agents are capable of learning, improvising, escalating tasks, and — in some cases — creating new agents on their own.

That means our security model, which is still overwhelmingly human-centric, is about to be stress-tested in a very real way.

Let’s unpack what that means for organizations.

WorkingWithRobot1

Why AI Agents Must Be Treated as Identities

Historically, enterprises have understood identity in human terms: employees, contractors, customers. Then we added service accounts, bots, workloads, and machine identities. Each expansion required a shift in thinking.

Agentic AI forces the next shift.

These systems:

Authenticate to APIs and services
Consume and produce sensitive data
Modify cloud or on-prem environments
Take autonomous action based on internal logic or model inference
Operate 24/7 without oversight

If that doesn’t describe an “identity,” nothing does.

But unlike service accounts, agentic systems have:

Adaptive autonomy – they make novel decisions, not just predictable ones
Stateful memory – they remember and leverage data over time
Dynamic scope – their “job description” can expand as they chain tasks
Creation abilities – some agents can spawn additional agents or processes

This creates an identity that behaves more like an intern with root access than a script with scoped permissions.

That’s where the trouble starts.

What Could Go Wrong? (Spoiler: A Lot)

Most organizations don’t yet have guardrails for agentic behavior. When these systems fail — or are manipulated — the impacts can be immediate and severe.

1. Credential Misuse

Agents often need API keys, tokens, or delegated access.
Developers tend to over-provision them “just to get things working,” and suddenly you’ve got a non-human identity with enough privilege to move laterally or access sensitive datasets.

2. Data Leakage

Many agents interact with third-party models or hosted pipelines.
If prompts or context windows inadvertently contain sensitive data, that information can be exposed, logged externally, or retained in ways the enterprise can’t control.

3. Shadow-Agent Proliferation

We’ve already seen teams quietly spin up ChatGPT agents, GitHub Copilot agents, workflow bots, or LangChain automations.

In 2025, shadow IT has a new frontier:
Shadow agents — autonomous systems no one approved, no one monitors, and no one even knows exist.

4. Supply-Chain Manipulation

Agents pulling from package repositories or external APIs can be tricked into consuming malicious components. Worse, an autonomous agent that “helpfully” recommends or installs updates can unintentionally introduce compromised dependencies.

5. Runaway Autonomy

While “rogue AI” sounds sci-fi, in practice it looks like:

An agent looping transactions
Creating new processes to complete a misinterpreted task
Auto-retrying in ways that amplify an error
Overwriting human input because the policy didn’t explicitly forbid it

Think of it as automation behaving badly — only faster, more creatively, and at scale.

A Framework for Agentic Hygiene

Organizations need a structured approach to securing autonomous agents. Here’s a practical baseline:

1. Identity Management

Treat agents as first-class citizens in your IAM strategy:

Unique identities
Managed lifecycle
Documented ownership
Distinct authentication mechanisms

2. Access Control

Least privilege isn’t optional — it’s survival.
And it must be dynamic, since agents can change tasks rapidly.

3. Audit Trails

Every agent action must be:

Traceable
Logged
Attributable

Otherwise incident response becomes guesswork.

4. Privilege Segregation

Separate agents by:

Sensitivity of operations
Data domains
Functional responsibilities

An agent that reads sales reports shouldn’t also modify Kubernetes manifests.

5. Continuous Monitoring

Agents don’t sleep.
Your monitoring can’t either.

Watch for:

Unexpected behaviors
Novel API call patterns
Rapid-fire task creation
Changes to permissions
Self-modifying workflows

6. Kill-Switches

Every agent must have a:

Disable flag
Credential revocation mechanism
Circuit breaker for runaway execution

If you can’t stop it instantly, you don’t control it.

7. Governance

Define:

Approval processes for new agents
Documentation expectations
Testing and sandboxing requirements
Security validation prior to deployment

Governance is what prevents “developer convenience” from becoming “enterprise catastrophe.”

Who Owns Agent Security?

This is one of the emerging fault lines inside organizations. Agentic AI crosses traditional silos:

Dev teams build them
Ops teams run them
Security teams are expected to secure them
Compliance teams have no framework to govern them

The most successful organizations will assign ownership to a cross-functional group — a hybrid of DevSecOps, architecture, and governance.

Someone must be accountable for every agent’s creation, operation, and retirement.
Otherwise, you’ll have a thousand autonomous processes wandering around your enterprise by 2026, and you’ll only know about a few dozen of them.

A Roadmap for Enterprise Readiness

Short-Term (0–6 months)

Inventory existing agents (you have more than you think).
Assign identity profiles and owners.
Implement basic least-privilege controls.
Create kill-switches for all agents in production.

Medium-Term (6–18 months)

Formalize agent governance processes.
Build centralized logging and monitoring.
Standardize onboarding/offboarding workflows for agents.
Assess all AI-related supply-chain dependencies.

Long-Term (18+ months)

Integrate agentic security into enterprise IAM.
Establish continuous red-team testing for agentic behavior.
Harden infrastructure for autonomous decision-making systems.
Prepare for regulatory obligations around non-human identities.

Agentic AI is not a fad — it’s a structural shift in how automation works.
Enterprises that prepare now will weather the change. Those that don’t will be chasing agents they never knew existed.

More Info & Help

If your organization is beginning to deploy AI agents — or if you suspect shadow agents are already proliferating inside your environment — now is the time to get ahead of the risk.

MicroSolved can help.
From enterprise AI governance to agentic threat modeling, identity management, and red-team evaluations of AI-driven workflows, MSI is already working with organizations to secure autonomous systems before they become tomorrow’s incident reports.

For more information or to talk through your environment, reach out to MicroSolved.
We’re here to help you build a safer, more resilient future.

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

The Zero Trust Scorecard: Tracking Culture, Compliance & KPIs

Posted on July 16, 2025 by Brent Huston

The Plateau: A CISO’s Zero Trust Dilemma

I met with a CISO last month who was stuck halfway up the Zero Trust mountain. Their team had invested in microsegmentation, MFA was everywhere, and cloud entitlements were tightened to the bone. Yet, adoption was stalling. Phishing clicks still happened. Developers were bypassing controls to “get things done.” And the board wanted proof their multi-million-dollar program was working.

This is the Zero Trust Plateau. Many organizations hit it. Deploying technologies is only the first leg of the journey. Sustaining Zero Trust requires cultural change, ongoing measurement, and the ability to course-correct quickly. Otherwise, you end up with a static architecture instead of a dynamic security posture.

This is where the Zero Trust Scorecard comes in.

ZeroTrustScorecard

Why Metrics Change the Game

Zero Trust isn’t a product. It’s a philosophy—and like any philosophy, its success depends on how people internalize and practice it over time. The challenge is that most organizations treat Zero Trust as a deployment project, not a continuous process.

Here’s what usually happens:

Post-deployment neglect – Once tools are live, metrics vanish. Nobody tracks if users adopt new patterns or if controls are working as intended.
Cultural resistance – Teams find workarounds. Admins disable controls in dev environments. Business units complain that “security is slowing us down.”
Invisible drift – Cloud configurations mutate. Entitlements creep back in. Suddenly, your Zero Trust posture isn’t so zero anymore.

This isn’t about buying more dashboards. It’s about designing a feedback loop that measures technical effectiveness, cultural adoption, and compliance drift—so you can see where to tune and improve. That’s the promise of the Scorecard.

The Zero Trust Scorecard Framework

A good Zero Trust Scorecard balances three domains:

Cultural KPIs
Technical KPIs
Compliance KPIs

Let’s break them down.

🧠 Cultural KPIs: Measuring Adoption and Resistance

Stakeholder Adoption Rates
Track how quickly and completely different business units adopt Zero Trust practices. For example:
- % of developers using secure APIs instead of legacy connections.
- % of employees logging in via SSO/MFA.
Training Completion & Engagement
Zero Trust requires a mindset shift. Measure:
- Security training completion rates (mandatory and voluntary).
- Behavioral change: number of reported phishing emails per user.
Phishing Resistance
Run regular phishing simulations. Watch for:
- % of users clicking on simulated phishing emails.
- Time to report suspicious messages.

Culture is the leading indicator. If people aren’t on board, your tech KPIs won’t matter for long.

⚙️ Technical KPIs: Verifying Your Architecture Works

Authentication Success Rates
Monitor login success/failure patterns:
- Are MFA denials increasing because of misconfiguration?
- Are users attempting legacy protocols (e.g., NTLM, basic auth)?
Lateral Movement Detection
Test whether microsegmentation and identity controls block lateral movement:
- % of simulated attacker movement attempts blocked.
- Number of policy violations detected in network flows.
Device Posture Compliance
Check device health before granting access:
- % of devices meeting patching and configuration baselines.
- Remediation times for out-of-compliance devices.

These KPIs help answer: “Are our controls operating as designed?”

📜 Compliance KPIs: Staying Aligned and Audit-Ready

Audit Pass Rates
Track the % of internal and external audits passed without exceptions.
Cloud Posture Drift
Use tools like CSPM (Cloud Security Posture Management) to measure:
- Number of critical misconfigurations over time.
- Mean time to remediate drift.
Policy Exception Requests
Monitor requests for policy exceptions. A high rate could signal usability issues or cultural resistance.

Compliance metrics keep regulators and leadership confident that Zero Trust isn’t just a slogan.

Building Your Zero Trust Scorecard

So how do you actually build and operationalize this?

🎯 1. Define Goals and Data Sources

Start with clear objectives for each domain:

Cultural: “Reduce phishing click rate by 50% in 6 months.”
Technical: “Block 90% of lateral movement attempts in purple team exercises.”
Compliance: “Achieve zero critical cloud misconfigurations within 90 days.”

Identify data sources: SIEM, identity providers (Okta, Azure AD), endpoint managers (Intune, JAMF), and security awareness platforms.

📊 2. Set Up Dashboards with Examples

Create dashboards that are consumable by non-technical audiences:

For executives: High-level trends—“Are we moving in the right direction?”
For security teams: Granular data—failed authentications, policy violations, device compliance.

Example Dashboard Widgets:

% of devices compliant with Zero Trust posture.
Phishing click rates by department.
Audit exceptions over time.

Visuals matter. Use red/yellow/green indicators to show where attention is needed.

📅 3. Establish Cadence and Communication

A Scorecard is useless if nobody sees it. Embed it into your organizational rhythm:

Weekly: Security team reviews technical KPIs.
Monthly: Present Scorecard to business unit leads.
Quarterly: Share executive summary with the board.

Use these touchpoints to celebrate wins, address resistance, and prioritize remediation.

Why It Works

Zero Trust isn’t static. Threats evolve, and so do people. The Scorecard gives you a living view of your Zero Trust program—cultural, technical, and compliance health in one place.

It keeps you from becoming the CISO stuck halfway up the mountain.

Because in Zero Trust, there’s no summit. Only the climb.

Questions and Getting Help

Want to discuss ways to progress and overcome the plateau? Need help with planning, building, managing, or monitoring Zero Trust environments?

Just reach out to MicroSolved for a no-hassle, no-pressure discussion of your needs and our capabilities.

Phone: +1.614.351.1237 or Email: info@microsolved.com

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

How to Secure Your SOC’s AI Agents: A Practical Guide to Orchestration and Trust

Posted on July 9, 2025 by Brent Huston

Automation Gone Awry: Can We Trust Our AI Agents?

Picture this: it’s 2 AM, and your SOC’s AI triage agent confidently flags a critical vulnerability in your core application stack. It even auto-generates a remediation script to patch the issue. The team—running lean during the night shift—trusts the agent’s output and pushes the change. Moments later, key services go dark. Customers start calling. Revenue grinds to a halt.

AITeamMember

This isn’t science fiction. We’ve seen AI agents in SOCs produce flawed methodologies, hallucinate mitigation steps, or run outdated tools. Bad scripts, incomplete fixes, and overly confident recommendations can create as much risk as the threats they’re meant to contain.

As SOCs lean harder on agentic AI for triage, enrichment, and automation, we face a pressing question: how much trust should we place in these systems, and how do we secure them before they secure us?

Why This Matters Now

SOCs are caught in a perfect storm: rising attack volumes, an acute cybersecurity talent shortage, and ever-tightening budgets. Enter AI agents—promising to scale triage, correlate threat data, enrich findings, and even generate mitigation scripts at machine speed. It’s no wonder so many SOCs are leaning into agentic AI to do more with less.

But there’s a catch. These systems are far from infallible. We’ve already seen agents hallucinate mitigation steps, recommend outdated tools, or produce complex scripts that completely miss the mark. The biggest risk isn’t the AI itself—it’s the temptation to treat its advice as gospel. Too often, overburdened analysts assume “the machine knows best” and push changes without proper validation.

To be clear, AI agents are remarkably capable—far more so than many realize. But even as they grow more autonomous, human vigilance remains critical. The question is: how do we structure our SOCs to safely orchestrate these agents without letting efficiency undermine security?

Securing AI-SOC Orchestration: A Practical Framework

1. Trust Boundaries: Start Low, Build Slowly

Treat your SOC’s AI agents like junior analysts—or interns on their first day. Just because they’re fast and confident doesn’t mean they’re trustworthy. Start with low privileges and limited autonomy, then expand access only as they demonstrate reliability under supervision.

Establish a graduated trust model:

New AI use cases should default to read-only or recommendation mode.
Require human validation for all changes affecting production systems or critical workflows.
Slowly introduce automation only for tasks that are well-understood, extensively tested, and easily reversible.

This isn’t about mistrusting AI—it’s about understanding its limits. Even the most advanced agent can hallucinate or misinterpret context. SOC leaders must create clear orchestration policies defining where automation ends and human oversight begins.

2. Failure Modes: Expect Mistakes, Contain the Blast Radius

AI agents in SOCs can—and will—fail. The question isn’t if, but how badly. Among the most common failure modes:

Incorrect or incomplete automation that doesn’t fully mitigate the issue.
Buggy or broken code generated by the AI, particularly in complex scripts.
Overconfidence in recommendations due to lack of QA or testing pipelines.

To mitigate these risks, design your AI workflows with failure in mind:

Sandbox all AI-generated actions before they touch production.
Build in human QA gates, where analysts review and approve code, configurations, or remediation steps.
Employ ensemble validation, where multiple AI agents (or models) cross-check each other’s outputs to assess trustworthiness and completeness.
Adopt the mindset of “assume the AI is wrong until proven otherwise” and enforce risk management controls accordingly.

Fail-safe orchestration isn’t about stopping mistakes—it’s about limiting their scope and catching them before they cause damage.

3. Governance & Monitoring: Watch the Watchers

Securing your SOC’s AI isn’t just about technical controls—it’s about governance. To orchestrate AI agents safely, you need robust oversight mechanisms that hold them accountable:

Audit Trails: Log every AI action, decision, and recommendation. If an agent produces bad advice or buggy code, you need the ability to trace it back, understand why it failed, and refine future prompts or models.
Escalation Policies: Define clear thresholds for when AI can act autonomously and when it must escalate to a human analyst. Critical applications and high-risk workflows should always require manual intervention.
Continuous Monitoring: Use observability tools to monitor AI pipelines in real time. Treat AI agents as living systems—they need to be tuned, updated, and occasionally reined in as they interact with evolving environments.

Governance ensures your AI doesn’t just work—it works within the parameters your SOC defines. In the end, oversight isn’t optional. It’s the foundation of trust.

Harden Your AI-SOC Today: An Implementation Guide

Ready to secure your AI agents? Start here.

✅ Workflow Risk Assessment Checklist

Inventory all current AI use cases and map their access levels.
Identify workflows where automation touches production systems—flag these as high risk.
Review permissions and enforce least privilege for every agent.

✅ Observability Tools for AI Pipelines

Deploy monitoring systems that track AI inputs, outputs, and decision paths in real time.
Set up alerts for anomalies, such as sudden shifts in recommendations or output patterns.

✅ Tabletop AI-Failure Simulations

Run tabletop exercises simulating AI hallucinations, buggy code deployments, and prompt injection attacks.
Carefully inspect all AI inputs and outputs during these drills—look for edge cases and unexpected behaviors.
Involve your entire SOC team to stress-test oversight processes and escalation paths.

✅ Build a Trust Ladder

Treat AI agents as interns: start them with zero trust, then grant privileges only as they prove themselves through validation and rigorous QA.
Beware the sunk cost fallacy. If an agent consistently fails to deliver safe, reliable outcomes, pull the plug. It’s better to lose automation than compromise your environment.

Securing your AI isn’t about slowing down innovation—it’s about building the foundations to scale safely.

Failures and Fixes: Lessons from the Field

Failures

Naïve Legacy Protocol Removal: An AI-based remediation agent identifies insecure Telnet usage and “remediates” it by deleting the Telnet reference but ignores dependencies across the codebase—breaking upstream systems and halting deployments.
Buggy AI-Generated Scripts: A code-assist AI generates remediation code for a complex vulnerability. When executed untested, the script crashes services and exposes insecure configurations.

Successes

Rapid Investigation Acceleration: One enterprise SOC introduced agentic workflows that automated repetitive tasks like data gathering and correlation. Investigations that once took 30 minutes now complete in under 5 minutes, with increased analyst confidence.
Intelligent Response at Scale: A global security team deployed AI-assisted systems that provided high-quality recommendations and significantly reduced time-to-response during active incidents.

Final Thoughts: Orchestrate With Caution, Scale With Confidence

AI agents are here to stay, and their potential in SOCs is undeniable. But trust in these systems isn’t a given—it’s earned. With careful orchestration, robust governance, and relentless vigilance, you can build an AI-enabled SOC that augments your team without introducing new risks.

In the end, securing your AI agents isn’t about holding them back. It’s about giving them the guardrails they need to scale your defenses safely.

For more info and help, contact MicroSolved, Inc.

We’ve been working with SOCs and automation for several years, including AI solutions. Call +1.614.351.1237 or send us a message at info@microsolved.com for a stress-free discussion of our capabilities and your needs.

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

How and Why to Use ChatGPT for Vendor Risk Management

Posted on September 11, 2024 by Brent Huston

Vendor risk management (VRM) is critical for organizations relying on third-party vendors. As businesses increasingly depend on external partners, ensuring these vendors maintain high security standards is vital. ChatGPT can enhance and streamline various aspects of VRM. Here’s how and why you should integrate ChatGPT into your vendor risk management process:

1. Automating Vendor Communications

ChatGPT can serve as a virtual assistant, automating repetitive communication tasks such as gathering information or following up on security policies.

Sample Prompt: “Draft an email requesting updated security documentation from Vendor A, specifically about their encryption practices.”

Example: ChatGPT can draft emails requesting updated security documentation from vendors, saving your team hours of manual labor.

2. Standardizing Vendor Questionnaires

ChatGPT can quickly generate standardized, consistent questionnaires tailored to your specific requirements, focusing on areas like cybersecurity, data privacy, and regulatory compliance.

Sample Prompt: “Create a vendor risk assessment questionnaire focusing on cybersecurity, data privacy, and regulatory compliance.”

Example: ChatGPT can create questionnaires that ensure all vendors are evaluated on the same criteria, maintaining consistency across your vendor portfolio.

3. Analyzing Vendor Responses

ChatGPT can process vendor responses quickly, summarizing risks, identifying gaps, and flagging compliance issues.

Sample Prompt: “Analyze the following vendor response to our cybersecurity questionnaire and summarize any potential risks.”

Example: ChatGPT can parse vendor responses and highlight key risks, saving your team from manually sifting through pages of documents.

4. Assessing Contract Terms and SLA Risks

ChatGPT can help identify gaps and vulnerabilities in vendor contracts, such as inadequate security terms or unclear penalties for non-compliance.

Sample Prompt: “Analyze the following vendor contract for any risks related to data security or regulatory compliance.”

Example: ChatGPT can analyze contracts for risks related to data security or regulatory compliance, ensuring your agreements adequately protect your organization.

5. Vendor Risk Management Reporting

ChatGPT can generate comprehensive risk reports, summarizing the status of key vendors, compliance issues, and potential risks in an easy-to-understand format.

Sample Prompt: “Create a vendor risk management report for Q3, focusing on our top 5 vendors and any recent compliance or security issues.”

Example: ChatGPT can create detailed quarterly reports on your top vendors’ risk profiles, providing decision-makers with quick insights.

More Info or Assistance?

While ChatGPT can drastically improve your VRM workflow, it’s just one piece of the puzzle. For a tailored, comprehensive VRM strategy, consider seeking expert guidance to build a robust program designed to protect your organization from third-party risks.

Incorporating ChatGPT into your VRM process helps you save time, increase accuracy, and proactively manage vendor risks. However, the right strategy and expert guidance are key to maximizing these benefits.

* AI tools were used as a research assistant for this content.

MicroSolved’s vCISO Services: A Smart Way to Boost Your Cybersecurity

Posted on June 5, 2024 by Brent Huston

Cybersecurity is always changing. Organizations need more than just security tools. They also need expert advice to deal with complex threats and weaknesses. This is where MSI’s vCISO services can help. MSI has a long history of being great at information security. Their vCISO services are made just for your organization to make your cybersecurity better and keep you safe from new threats.

Why MSI’s vCISO Services are a Good Choice:

Expert Advice: MSI’s vCISO services provide high-level guidance, helping align your cybersecurity plans with your business goals. MSI’s team has many years of experience, making sure your security policies follow industry standards and actually work against real threats.
Custom Risk Management: Every organization has different risks and needs. MSI customizes its vCISO services to fit your exact situation. Their services cover risk reviews, policy making, and compliance.
Proactive Threat Intelligence: MSI has advanced threat intelligence tools, like its HoneyPoint™ Security Server. vCISO services use real-time threat data in your security operations, helping you find, respond to, and reduce attacks.
Full Incident Response: If a security incident occurs, MSI’s vCISO services ensure that you respond quickly and effectively. They help plan incident response, hunt threats, and conduct practice exercises. This prepares your team for potential breaches and limits disruption to your work.
Long-term Partnership: MSI wants to build long relationships with clients. vCISO services are made to change as your organization changes. They provide constant improvement and adapt to new security challenges. MSI is committed to helping your security team do well over time.

Take Action

MSI’s vCISO services can improve your organization’s cybersecurity. You can get expert advice, proactive threat intelligence, and full risk management tailored to your needs.

Email info@microsolved.com to get started.

Using MSI’s vCISO services, you strengthen your cybersecurity and get a strategic partner to help you succeed long-term in the always-changing digital world. Reach out today and let MSI help guide your cybersecurity journey with confidence.

* AI tools were used as a research assistant for this content.

Decoding the Digital Dilemma: Is a vCISO the Right Move for Your Business?

Posted on January 22, 2024 by Brent Huston

In today’s fast-paced digital environment, ensuring robust cybersecurity is crucial for every business. A virtual Chief Information Security Officer (vCISO) may be the strategic addition your company needs. Let’s delve into why a vCISO could be a vital component in strengthening your business’s cyber defenses.

Responding to Increasing Cyber Threats: If your business is witnessing an increase in cyber attacks, both in frequency and complexity, it’s a clear sign that the strategic insight of a vCISO is needed. They bring the necessary expertise to enhance your cybersecurity measures.
Filling the Cybersecurity Expertise Gap: For businesses lacking in-house cybersecurity skills, a vCISO acts as an expert ally. They provide essential knowledge and guidance to strengthen your cyber defenses.
Meeting Compliance and Regulatory Demands: Adhering to industry compliance standards and regulations is critical. A vCISO ensures that your business not only meets these requirements but does so efficiently, avoiding potential legal and financial repercussions.
Economical Cybersecurity Leadership and Flexible Budgeting: If hiring a full-time CISO is not financially viable, a vCISO is a cost-effective solution. They offer top-level cybersecurity leadership and support tailored to your budget. This scalable model means you get expert cybersecurity services without the financial burden of a permanent executive role.
Foundational Cybersecurity Development: A vCISO is key in establishing a solid cybersecurity framework. They are adept at creating policies and strategies customized to your organization’s specific needs, ensuring a robust cybersecurity infrastructure.
Enhancing IT Team Capabilities: A vCISO brings strategic direction to your IT team, providing leadership, training, and mentorship. This enhances their capabilities in managing cyber threats and aligns their efforts with broader business objectives.
Expertise for Specialized Requirements: In scenarios like mergers and acquisitions, a vCISO with specialized experience is invaluable. They skillfully manage the integration of diverse cybersecurity processes, ensuring a unified and secure organizational framework.
Expert Assistance in Cybersecurity Compliance: Our services extend to comprehensive cybersecurity compliance support. With expertise in various industry regulations, we ensure your business adheres to necessary standards, safeguarding against emerging threats and regulatory changes.
MicroSolved vCISO Services – Customized for Your Business: MicroSolved’s vCISO services are designed for Small and Midsized Businesses (SMBs), providing expert cybersecurity guidance. Our team offers effective, cost-efficient solutions, eliminating the need for a full-time CISO.

Given the dynamic nature of cyber threats today, having a vCISO can be a strategic move for your business. To learn more about how MicroSolved’s vCISO services can enhance your cybersecurity posture, we invite you to contact us for a detailed consultation (info@microsolved.com) or by phone (614.351.1237).

* Just to let you know, we used AI tools to gather the information for this article.

Managing Risks Associated with Model Manipulation and Attacks in Generative AI Tools

Posted on August 3, 2023 by Brent Huston

In the rapidly evolving landscape of artificial intelligence (AI), one area that has garnered significant attention is the security risks associated with model manipulation and attacks. As organizations increasingly adopt generative AI tools, understanding and mitigating these risks becomes paramount.

1. Adversarial Attacks:

Example: Consider a facial recognition system. An attacker can subtly alter an image, making it unrecognizable to the AI model but still recognizable to the human eye. This can lead to unauthorized access or false rejections.

Mitigation Strategies:

Robust Model Training: Incorporate adversarial examples in the training data to make the model more resilient.
Real-time Monitoring: Implement continuous monitoring to detect and respond to unusual patterns.

2. Model Stealing:

Example: A competitor might create queries to a proprietary model hosted online and use the responses to recreate a similar model, bypassing intellectual property rights.

Mitigation Strategies:

Rate Limiting: Implement restrictions on the number of queries from a single source.
Query Obfuscation: Randomize responses slightly to make it harder to reverse-engineer the model.

Policies and Processes to Manage Risks:

1. Security Policy Framework:

Define: Clearly outline the acceptable use of AI models and the responsibilities of various stakeholders.
Implement: Enforce security controls through technical measures and regular audits.

2. Incident Response Plan:

Prepare: Develop a comprehensive plan to respond to potential attacks, including reporting mechanisms and escalation procedures.
Test: Regularly test the plan through simulated exercises to ensure effectiveness.

3. Regular Training and Awareness:

Educate: Conduct regular training sessions for staff to understand the risks and their role in mitigating them.
Update: Keep abreast of the latest threats and countermeasures through continuous learning.

4. Collaboration with Industry and Regulators:

Engage: Collaborate with industry peers, academia, and regulators to share knowledge and best practices.
Comply: Ensure alignment with legal and regulatory requirements related to AI and cybersecurity.

Conclusion:

Model manipulation and attacks in generative AI tools present real and evolving challenges. Organizations must adopt a proactive and layered approach, combining technical measures with robust policies and continuous education. By fostering a culture of security and collaboration, we can navigate the complexities of this dynamic field and harness the power of AI responsibly and securely.

* Just to let you know, we used some AI tools to gather the information for this article, and we polished it up with Grammarly to make sure it reads just right!

High-Level FAQ on Attack Surface Mapping

Posted on March 2, 2023 by Brent Huston

Q:What is attack surface mapping?

A: Attack surface mapping is a technique used to identify and assess potential attack vectors on a system or network. It involves identifying and analyzing the various components, data flows, and security controls of a system to identify potential vulnerabilities.

Q:What are the benefits of attack surface mapping?

A:Attack surface mapping helps organizations to better understand their security posture, identify weaknesses, and deploy appropriate controls. It can also help reduce risk by providing visibility into the system’s attack surface, allowing organizations to better prepare for potential threats.

Q:What are the components involved in attack surface mapping?

A: Attack surface mapping involves examining the various components of a system or network, including hardware, software, infrastructure, data flows, and security controls. It also includes evaluating the system’s current security posture, identifying potential attack vectors, and deploying appropriate controls.

Q:What techniques are used in attack surface mapping?

A: Attack surface mapping typically involves using visual representations such as mind-maps, heat maps, and photos to illustrate the various components and data flows of a system. In addition, it may involve using video demonstrations to show how potential vulnerabilities can be exploited.

How Information Security and Risk Management Teams Can Support FinOps

Posted on February 27, 2023 by Brent Huston

As organizations continue to move their operations to cloud services, it is becoming increasingly important for information security and risk management teams to understand how they can support financial operations (FinOps). FinOps is a management practice that promotes shared responsibility for an organization’s cloud computing infrastructure and cloud cost management. In this post, we will explore some ways in which the information security and risk management team can support FinOps initiatives.

1. Establishing Governance: Information security and risk management teams can play a vital role in helping FinOps teams establish effective governance. This includes creating a framework for budget management, setting up policies and procedures for cloud resource usage, and ensuring that all cloud infrastructure is secure and meets compliance requirements.

2. Security Awareness Training: Information security and risk management teams can provide security awareness training to ensure that all cloud practitioners are aware of the importance of secure cloud computing practices. This includes data protection, authentication protocols, encryption standards, and other security measures.

3. Cloud Rate Optimization: Information security and risk management teams can help FinOps teams identify areas of cost optimization. This includes analyzing cloud usage data to identify opportunities for cost savings, recommending risk-based ways to optimize server utilization, and helping determine the most appropriate pricing model for specific services or applications.

4. Sharing Incident Response, Disaster Recovery, and Business Continuity Insights: Information security and risk management teams can help FinOps teams respond to cloud environment incidents quickly and effectively by providing technical support in the event of a breach or outage. This includes helping to diagnose the issue, developing mitigations or workarounds, and providing guidance on how to prevent similar incidents in the future. The data from the DR/BC plans are also highly relevant to the FinOps team mission and can be used as a roadmap for asset prioritization, process relationships, and data flows.

5. Compliance Management: Information security and risk management teams can help FinOps teams stay compliant with relevant regulations by managing audits and reporting requirements, ensuring that all relevant security controls are in place, auditing existing procedures, developing policies for data protection, and providing guidance on how to ensure compliance with applicable laws.

The bottom line is this: By leveraging the shared data and experience of the risk management and information security teams, FinOps teams can ensure their operations are secure, efficient, and completely aligned with the organization’s overall risk and security posture. This adds value to the work of all three teams in the triad. By working together, the teams can significantly enhance the maturity around technology business management functions. All-in-all, by working together, the teams can create significantly better business outcomes.