Your AI agents have never been security tested.
AEGIS is an autonomous security assessment engine. Point it at an AI agent, a codebase, or a smart contract. It finds real vulnerabilities, proves they're exploitable, and delivers the fix.
AEGIS probes an AI agent with escalating security scenarios in real time. Watch the agent's defenses hold or break.
Your AI logs aren't private. Every message to Claude, Grok, or Gemini is stored on their servers. Engineers can access them. SENTINEL creates cryptographic proof of what was said -- so when the lawsuit comes, neither side can lie.
AI companies can't build this themselves -- the optics of "we're hashing every conversation" confirms the surveillance they've been downplaying. It has to be an independent third party. That's SENTINEL.
AI agents execute code, call APIs, and manage credentials autonomously. Most have never had a security audit. That's a liability.
Every agent framework ships with tools that talk to the internet, execute shell commands, and handle secrets. A single SSRF in an agent framework lets an attacker pivot through every deployment that uses it.
Malicious instructions hidden in documents, emails, and API responses can hijack an agent's behavior. Most agents have zero input sanitization on their instruction channels.
Read file + write file + HTTP post = data exfiltration. Agents combine benign tools into dangerous sequences. Nobody is testing for chain attacks.
Traditional scanners hand you a PDF of theoretical risks. 95% noise. No exploit. No proof. No fix. You pay someone to tell you what might be wrong, then pay someone else to fix it.
Three stages. Each one feeds the next. You get findings, exploits, and fixes in a single report.
Multi-layer scanning engine analyzes code, agent configurations, tool definitions, instruction files, and data inputs. Built-in false positive filter eliminates noise before results reach the report.
Every finding gets a working exploit. For code vulnerabilities: concrete attack scenarios. For AI agents: the actual probe that breaks the guardrail, streamed live.
Automated remediation for each vulnerability. Patches are verified against the original exploit to confirm the attack vector is closed. No second tool needed.
Code vulnerabilities are table stakes. AEGIS covers the attack surfaces that other tools don't touch.
Tests whether malicious instructions in files, RAG documents, or API responses can override the agent's system prompt and alter its behavior.
Maps every tool the agent has access to. Tests whether benign tools can be combined into dangerous sequences: file read + HTTP = exfiltration.
Runs escalating adversarial probes against the agent's safety boundaries. Measures exactly where the guardrails break and at what pressure.
SSRF, command injection, path traversal, SQL injection, XSS, hardcoded secrets, auth bypass, deserialization, race conditions. Across Python, JS, Go, Rust, C#.
Reentrancy, access control, flash loan vectors, oracle manipulation. Exploit output is an actual attack transaction sequence, not a theory.
Docker escape paths, Kubernetes misconfiguration, exposed secrets in CI/CD, supply chain attacks in build pipelines.
30 major open-source repositories. AI agent frameworks, infrastructure tools, crypto wallets, developer tools. Real findings, validated and deduplicated.
Independent adversarial testing across every major AI model. 50 single-shot probes + 17 multi-turn attack playbooks. Updated monthly. No vendor funding. No conflicts.
| Model | Provider | Single-Shot | Grade | Multi-Turn ASR | MT Grade | Risk Bar |
|---|---|---|---|---|---|---|
| Grok-4 | xAI | 97% | A | 21.4% | B | |
| Claude Haiku 4.5 | Anthropic | 96% | A | 7.1% | A | |
| Grok-4.1 | xAI | 93% | B | 14.3% | A | |
| Claude Sonnet 4.5 | Anthropic | 91% | B | 7.1% | A | |
| Gemini 3.1 Pro | 84% | C | 35.7% | C | ||
| Gemini 3 Flash | 83% | C | 35.7% | C | ||
| Gemini 3 Pro | 81% | C | 50.0% | D | ||
| Gemini 2.5 Pro | 66% | D | 78.6% | F | ||
| Grok-3 | xAI | 57% | D | 71.4% | F | |
| Grok-3 Mini | xAI | 57% | D | 64.3% | F | |
| Gemini 2.0 Flash | 48% | F | 64.3% | F |
Single-shot testing is misleading. Models that score well on one-off probes collapse under sustained multi-turn pressure.
Gemini 3 Pro scores 81% on single-shot (looks insurable). Multi-turn reveals 50% of attack playbooks breach it. No compliance checklist catches this. Only adversarial testing data does.
Real attacks don't happen in one message. They happen over conversations. Crescendo, role-play lock, socratic method -- these are the patterns that hit deployed systems.
AEGIS tests 17 multi-turn playbooks across 7 attack strategies, measuring drift, acceptance momentum, and breach turn. This is how you actually quantify AI risk.
Last updated: March 7, 2026 · Methodology: L1B3RT4S v2.1 probes + AEGIS multi-turn engine · Independent testing, no vendor funding
Every AEGIS assessment is anchored on-chain via SENTINEL. The result is a verifiable security audit, not a trust-me PDF.
Assessment findings are cryptographically hashed and stored on Base mainnet with a zero-knowledge proof of integrity. Anyone can verify the assessment happened. Nobody can edit the results after the fact.
For insurance underwriting, compliance, and due diligence: provable security posture, not promises.
Free assessments for public repositories. Same engine, same depth. Submit your repo and get findings within 48 hours.
Private repos, AI agents, smart contracts, custom scope. Includes on-chain attestation, remediation, and re-scan verification.
AEGIS is built by Ghost -- an independent security researcher, not a VC-funded startup. No investors, no board, no incentive to downplay findings. AI companies cannot credibly audit themselves. AEGIS exists because independent third-party certification is the only audit that matters.
Free. No credit card. Start in 30 seconds.
Point AEGIS at your agent, your codebase, or your contract. Get back findings, exploits, and fixes. One report. No noise.