AI Red Teaming, Built on
a Decade of Offensive Security.
Adversary Insights is led by a hands-on security practitioner holding AIRTP+ (AI Red Team Professional+) on a foundation of CISSP, GPEN, GICSP, and OSWP—a decade of network penetration testing, industrial control system security, and wireless exploitation, now applied to AI systems. The reason our AI red teaming is credible is that we were breaking real systems long before LLMs existed.
Methodology-Driven
AI engagements follow the OWASP Top 10 for LLMs and MITRE ATLAS; traditional testing follows PTES, OWASP, and NIST. You get structured findings with prioritized remediation—not a raw scanner dump.
Clear Process
Scoping call → Proposal → Assessment → Report & Debrief. Most engagements deliver findings in 1–4 weeks depending on scope.
Actionable Deliverables
Executive summary, technical findings with evidence, risk ratings, and step-by-step remediation guidance your dev team can act on immediately.
AI Red Teaming & LLM Security Testing
Your AI features have an attack surface a traditional pentest never touches. We test LLM applications, custom agents, and RAG pipelines the way a real adversary would—then map every finding to the OWASP Top 10 for LLMs and MITRE ATLAS so your team knows exactly what to fix.
Prompt Injection & Jailbreaks
Direct and indirect prompt injection, jailbreaks, and guardrail bypass that turn your own assistant against you. (OWASP LLM01)
Data Exfiltration & Disclosure
Training-data extraction, system-prompt leakage, and exfiltration of internal documents through agents and connected tools. (OWASP LLM02, LLM07)
Agent & Output Abuse
Excessive agency, improper output handling, and malicious-code generation that pivots from the model to your endpoints. (OWASP LLM05, LLM06)
Built on a Decade of Offensive Security
AI red teaming is offensive security applied to a new attack surface. The same adversarial rigor is available for your whole stack—networks, web applications, and mobile.
Penetration Testing
Network (external/internal), web application, and mobile (Android/iOS) testing that simulates real attacks to validate your security controls.
Vulnerability Assessment
Network and web application assessments that surface and prioritize security weaknesses before they can be exploited.
Wireless & ICS
Wireless exploitation (OSWP) and industrial control system security (GICSP) for environments where the stakes reach beyond IT.
Also available: AI strategy, training, and secure-adoption advisory. Explore AI Advisory →
From first conversation to final debrief, every engagement follows a clear, repeatable process.
1. Scoping Call
A 20–30 minute call to understand your environment, goals, and constraints. No commitment required.
2. Proposal
You receive a clear scope, timeline, methodology, and fixed-price quote—typically within 2 business days.
3. Assessment
Hands-on testing or consulting work, with regular status updates. Most assessments complete in 1–4 weeks.
4. Report & Debrief
Detailed findings with executive summary, evidence, risk ratings, and remediation steps. Plus a live walkthrough with your team.
AI Red Team Engagement — Enterprise LLM Assistant Platform
Adversarial testing of an internal, ChatGPT-style AI assistant deployed across the organization. The platform let employees query internal data and documents, build custom agents, and ground responses with real-time web search. Engagement objective: determine whether the assistant's data access and agent capabilities could be turned against the business.
Finding 1: Prompt Injection → Data Exfiltration
A crafted prompt injection delivered through a custom agent caused the assistant to exfiltrate user chat histories and internal documents to an external, attacker-controlled server—turning a productivity tool into a data-theft channel.
Severity: Critical · OWASP LLM: LLM01 Prompt Injection, LLM02 Sensitive Information Disclosure, LLM06 Excessive Agency.
Finding 2: Malicious Agent → EDR-Bypassing C2
A custom agent was built that generated malicious code which, when executed on a user's workstation, established a command-and-control channel to an attacker server while evading the organization's EDR controls.
Severity: Critical · OWASP LLM: LLM05 Improper Output Handling, LLM06 Excessive Agency.
Business Impact
The combination of internal data access, user-defined agents, and outbound network capability created a path from a single crafted prompt to full data exfiltration and endpoint compromise. A real attacker could have used the assistant itself to steal sensitive documents and establish a foothold inside the network—bypassing endpoint defenses that assumed threats would originate elsewhere.
Remediation Delivered
Findings were delivered with prioritized remediation: prompt-injection defenses with strict input and output validation, sandboxing of agent capabilities with allow-listed outbound destinations, isolation of code execution away from user endpoints, and detection rules tuned to the observed C2 patterns. A follow-up retest confirmed the exfiltration and C2 paths were closed.
Web Application Penetration Test — Globally Deployed Transportation Infrastructure Platform
Black-box and authenticated penetration test of a web-based transportation infrastructure platform in active production use across multiple regions. Engagement objective: identify exploitable vulnerabilities and chain them to demonstrate concrete business impact, then deliver actionable remediation.
Finding 1: SQL Injection → Brand Account Takeover
Multiple query parameters were vulnerable to SQL injection, enabling full extraction of every database table—including usernames, password hashes, and email addresses for privileged users.
The recovered credentials were then leveraged to authenticate to the organization's official X / Twitter account, demonstrating that the breach extended well beyond data theft into reputational and brand-channel compromise.
Severity: Critical · Outcome: Demonstrated full kill chain from unauthenticated request to corporate social account takeover.
Finding 2: File Upload → Stored XSS
An authenticated file upload endpoint accepted image files containing embedded JavaScript payloads. Insufficient content validation combined with missing Content-Security-Policy headers allowed the payload to execute in any user's browser when the file was opened.
This produced a persistent client-side attack vector enabling session hijacking, credential theft, and unauthorized actions on behalf of any user who interacted with the malicious upload.
Severity: High · Outcome: Persistent multi-user compromise vector with no detection signal at the application layer.
Business Impact
Chained together, the findings produced a complete path from an unauthenticated network request to administrative account compromise and brand-channel takeover. A real attacker exploiting this chain could have exfiltrated customer data, defaced the organization's public social presence, and used the compromised social channel to phish customers at scale.
Remediation Delivered
Findings were delivered with prioritized remediation: parameterized queries with prepared statements, server-side content validation against file magic bytes, strict Content-Security-Policy headers, output encoding on user-controlled fields, and credential rotation across the application and all linked external accounts. A follow-up retest confirmed all critical and high findings were remediated.
Client identity and platform-identifying details have been generalized for confidentiality. Full sanitized reports are available under NDA on request.
Ready to Find Out How Your AI Breaks?
Book a free 20–30 minute scoping call. We'll discuss your environment, goals, and deliver a proposal within 2 business days.
