More agents can share the same blind spot.
An agent can mistake a sign-in check for an ownership check, overlook a control in another file, or assume a value is safe without following it to the operation that uses it. A second agent working from the same incomplete context can repeat the mistake. The result can be an unsupported alert or a real vulnerability that goes unreported.
Splitting an audit among agents helps distribute work. It does not, by itself, establish which paths were covered, which protections actually execute, or whether a proposed patch closes the original weakness. A convincing report can still leave developers to reconstruct the evidence.
Some agent-led systems use deterministic tools and reproduce exploits. Those checks strengthen their results. The limitation arises wherever model judgment or agreement is used in place of evidence that establishes the claim.
Reachable path · relevant controls · observed or derived result
Conceptual workflow. Agent teams vary in their tools, testing methods, and validation.
Galen separates detection from the model’s opinion.
Built for web applications, Galen retains a structured map of entry points, call paths, data access, and security controls. Deterministic analysis derives findings from those facts and verifies their derivation. Where an access baseline has been reviewed and approved, changes can also be checked against that intent. AI helps explain findings and support remediation.
This directly addresses the shared-assumption problem. Whether a guard exists, which operation it governs, and how a value reaches that operation are questions for the code evidence. Another agent agreeing with the explanation is not required to make that evidence valid.
Consider an invoice endpoint that requires sign-in but accepts any customer’s invoice ID. The important distinction is between authentication and ownership. Galen’s evidence connects the lookup, the caller’s path, and the missing boundary so your team can inspect why the finding follows.
- Claim
- A customer can reach another customer’s invoice.
- Entry point
- Invoice endpoint → record lookup → response
- Expected boundary
- The invoice belongs to the caller’s tenant.
- Observed control
- Sign-in is checked; tenant ownership is not.
- Correction
- Enforce the tenant boundary at the lookup.
- Recheck
- Evaluate the corrected path and record the outcome.
Illustrative evidence summary, not actual Galen output.
A stronger basis for the security decision.
| Review question | When agent reasoning is the authority | Galen |
|---|---|---|
| Why is this a finding? | The model infers a weakness from the context it receives. | Deterministic analysis derives the finding from retained code facts and checks that derivation. |
| Does a control block the path? | A model may assume a helper or an earlier check provides the required protection. | Path and control evidence establish which protection applies to the sensitive operation. |
| Can the team inspect the reasoning? | An explanation may leave the underlying code relationships for developers to reconstruct. | The finding carries bounded evidence about the path, data, and controls. |
| What establishes the correction? | A plausible patch or a second agent’s approval can leave the original issue unresolved. | Re-analysis of the changed code lets reviewers check the affected security path against the original finding. |
The advantage is a code-security decision that rests on inspectable facts rather than agent consensus. Tools that also provide independent evidence should be evaluated on that evidence, not on the number of agents they deploy.
Give the coding agent evidence it can act on.
Galen narrows the handoff to the affected path, the relevant control, and the correction objective. Your developer or coding agent can work on the cause of the issue, then recheck the changed implementation. The application map, finding evidence, and approved policy baseline remain available across review conversations and coding assistants. Later checks examine the current code against that reference.
Galen Security brings this approach to deeper application audits. Galen Policy brings supported checks into development and compares access changes with the baseline your team approved, helping catch policy drift as code changes.
Coverage still depends on the supported stack and available evidence. Galen keeps proof gaps visible, so a reviewer can distinguish what the analysis establishes from what needs more context or runtime testing.