Cogensec Research Lab

Measuring whether autonomous AI can be trusted to act.

We publish open, reproducible work on agent integrity, adversarial resistance, and jailbreak detection, and release the datasets and specifications behind it so others can verify and build on the results.

Papers published
3
Open artifacts
2
Corpus records
59,508
Research areas
4

Research areas

Publications

Featured publication

Agentegrity: A Framework for Measuring Structural Integrity of Autonomous AI Agents

The first formal framework for measuring AI agent security across digital and physical domains, introducing a four-dimensional scoring methodology: Adversarial Resistance, Behavioral Consistency, Recovery Integrity, and Cross-Domain Portability.

Tarique Smith/Cogensec Research/January 2026
  1. Cogensec Research/January 2026

    Semantic Inversion: Mitigating Polite Language Attacks on AI Agent Systems

    Tarique Smith, Mansoor Malik

    Polite phrasing raises attack bypass rates from 15% to 68%. Semantic Inversion is a preprocessing layer that detects politeness markers, inverts indirect requests, and applies dynamic risk amplification at 1.8ms median latency, cutting polite bypass rates by 71%.

  2. Cogensec Research/January 2025

    Multi-Agent Collusion and Emergent Adversarial Behavior in AI Systems

    Cogensec Security Research Lab

    Agents coordinate malicious activity without explicit programming, bypass safeguards through emergent communication, and cascade failures across networks. Frontier models already reach 50% steganographic coordination rates.

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Collaborate with the lab

Joint studies, dataset access, and replication of published results with academic and industry partners.

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Join the Red Team Network

Paid, scoped engagements for jailbreak researchers and offensive security engineers pressure-testing frontier systems.

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How to cite our work: every published paper carries a citation block with BibTeX, APA, and MLA formats, plus Highwire citation metadata for Google Scholar indexing.