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Mythos
Myth or Reality!

What can you do today to prepare your organization for when Mythos becomes widely accessible? AI-driven attacks are becoming a reality, making stronger security, identity protection, and resilient infrastructure more important than ever.

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Mythos — Myth or Reality AI security defense in depth

Mythos - Myth or Reality


MYTH – the sky is falling
  • Mythos will instantly hack every system — there's nothing you can do to stop it
  • Mythos is locked away safely — restricted access means we're all protected for now
  • AI creates brand new vulnerabilities that never existed before
  • AI attacks are unstoppable because they operate at superhuman speed
  • Traditional security tools are obsolete in the age of AI
REALITY – basics still win
  • Mythos targets weak posture - MFA, least privilege, and patching stop most attacks cold
  • Similar capabilities are spreading to other labs and open-weight models - restricted access is a window, not a wall
  • AI exposes existing flaws faster - your unpatched CVEs are the real threat
  • Speed amplifies both sides - automated detection, rate limiting, and anomaly monitoring can shut down attacks just as fast
  • Your stack still matters - EDR, WAF, IAM, and SIEM become even more effective when tuned and integrated properly


Security That Actually Stops AI-Driven Attacks


Build-time Hygiene (SBOM, Patching Dependencies)

Your first line of defense starts before deployment. Eliminate common security gaps early in the development lifecycle.

  • Maintain SBOM for all services
  • Track and update vulnerable dependencies regularly
  • Auto-patch critical CVEs
  • Use trusted sources for libraries and AI models only
  • Secrets management using secure vaults
  • Least privilege IAM implementation
  • Enforce SSO + MFA for all access
  • Validate configurations and exposed services


Black-box Testing (Attacker Mindset)

Assume exposure and continuously test your environment like a real attacker would. Identify exploitable weaknesses before threat actors do.

  • Run regular internal and external penetration tests
  • Fuzz APIs and user inputs
  • Test prompt injection and data exfiltration risks
  • Abuse rate limits to uncover weaknesses
  • Validate authentication bypass scenarios
  • Simulate real-world attacker flows
  • Test exposed endpoints and misconfigurations
  • Adopt a continuous attacker mindset


SAST (Code-level Security)

Detect vulnerabilities before runtime by integrating automated and manual security checks directly into your development workflows.

  • Run SAST in local development and CI/CD pipelines
  • Scan repositories for hardcoded secrets
  • Identify SQL injection and command injection issues
  • Validate input sanitization paths
  • Review authentication and access control logic
  • Use security-focused linters and rulesets
  • Enforce secure coding standards
  • Perform manual reviews for critical code flows


User & Identity Hygiene

Identity remains the most exploited attack surface. Strengthen authentication, privilege management, and credential hygiene across your organization.

  • Enforce phishing-resistant MFA
  • Use unique passwords for every application
  • Apply least privilege access controls
  • Conduct periodic access reviews
  • Rotate API keys, tokens, and credentials regularly
  • Monitor unauthorized identity usage patterns

👉 "Identity is the new perimeter—and attackers know it."



Infrastructure & Runtime Defense

Protect live environments with continuous monitoring, segmentation, encryption, and adaptive access controls built for modern AI-driven threats.

  • Segment critical and non-critical networks
  • Keep infrastructure patched and updated
  • Encrypt sensitive business and customer data
  • Use context-aware access controls
  • Enable behavioral monitoring and anomaly detection
  • Integrate SIEM for centralized threat visibility

👉 "Speed cuts both ways—defenders can automate too."

Controlling AI Risk - Visibility, Governance, Guardrails

AGENT TRAFFIC DETECTION GOVERNANCE LLM GUARDRAILS
What it means Identify and monitor AI agents interacting with your systems. Define and enforce rules for how AI is used in your org. Runtime protections that filter, validate, and constrain AI inputs and outputs.
Why it matters AI agents can scale attacks or misuse rapidly. Visibility first. Prevent data leakage, ensure compliance, and avoid shadow AI. Stops prompt injection, prevents data exfiltration, and keeps outputs aligned with policy.
How it's done Behavior analysis, fingerprints, API gateways, and correlation. Access control, policies, logging, audit trails, and approval workflows. Input/output filtering, context isolation, policy rules, and retrieval constraints.
Think Think: Who/what is actually calling my system? Think: Are we using AI responsibly and within boundaries? Think: Even if something goes wrong, the AI stays within safe boundaries.


date

14+

Years of Experience

Pre-built Integrations

6000+

Pre-built Integrations



Clients Globally

30k+

Clients Globally

Cost saving

50%

Cost-saving

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