Multi-Agent Adversarial Code Audit
3 AI agents. Independent audits. Cross-verified results. The false positives don't survive.
The Pentest Illusion
Traditional security audits have a dirty secret: a single team reviews your code once, produces a report full of inflated findings, and charges $10K–$50K.
The result? P0 findings that aren't real P0s. Critical vulnerabilities buried in noise. No way to distinguish genuine threats from padding.
A single reviewer — human or AI — has blind spots. The only way to eliminate them is adversarial cross-verification by independent parties who don't trust each other.
The Karon 3-Agent Pipeline
-
Agent Alpha (Attack)
4 independent AI auditors scan the full codebase. Each produces severity-rated findings with line-number evidence. -
Agent Beta (Re-evaluation)
Second AI agent challenges every finding. Reads the actual code, verifies claims, re-rates severity. Identifies risks the first agent missed. -
Agent Gamma (Cross-Verdict)
Third AI agent trusts neither Alpha nor Beta. Independent code verification. Final severity ruling per finding. AGREE / DISAGREE / PARTIAL for each claim.
Real Audit Results
Karon API — 17 files, 3,700 LOC
Not a simulation. These are production findings from our own codebase.
| Phase | Agent | Findings | P0 | P1 | FP Rate |
|---|---|---|---|---|---|
| Attack | Agent Alpha (Kimi ×4) | 35 | 4 | 13 | — |
| Re-evaluate | Agent Beta (Claude) | 24 (11 dismissed) | 0 | 3 | 31% |
| Cross-Verify | Agent Gamma (GPT) | 20 (4 more dismissed) | 0 | 1 | 71% cumulative |
71% of original findings were false positives or severity inflation.
A traditional single-agent audit would have shipped all 35 as-is.
Audit Pipeline
Severity-rated findings
Line-number evidence
Re-rate severity
+4 missed risks found
Final severity ruling
AGREE / DISAGREE / PARTIAL
Traditional Pentest vs Karon Adversarial Audit
| Traditional Pentest | Karon 3-Agent Audit | |
|---|---|---|
| Reviewers | 1 team, 1 pass | 3 independent AI agents |
| Duration | 2–4 weeks | Hours |
| Cost | $10K – $50K | Fraction |
| FP Filtering | Report accepted as-is | 71% FP detection |
| Reproducibility | Non-reproducible | Deterministic, re-runnable |
| Evidence | Narrative descriptions | Line-number code references |
| Cross-Verification | None | Adversarial 3-party verdict |
| Scope | Sample-based | Full codebase |
Deliverables
Finding Report
- Per-finding severity (P0–P3)
- Code line references
- 3-agent verdict (AGREE / DISAGREE / PARTIAL)
- False positive rate
Action Priority
- Top 5 ranked by real-world impact
- Accepted risk documentation
- Architecture-level recommendations
Verification Artifact
- Full audit trail (reproducible)
- Agent disagreement analysis
- Re-runnable on code changes
Ready to Audit?
Ship with confidence. Know exactly what's real and what's noise.
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