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02/08/2026 11:57 am
TL;DR: Security teams need deterministic tools for repeatable, auditable results in CI/CD, while AI reasoning is better suited to triage, exploitability analysis, and novel vulnerability discovery, according to Aikido. The practical takeaway is that durable security posture comes from placing pattern matchers and probabilistic tools in the right order, not replacing one with the other.
NHIMG editorial — based on content published by Aikido: Why Determinism Is Still a Necessity in Security
Questions worth separating out
Q: How should security teams combine deterministic scanning with AI triage?
A: Use deterministic scanning for continuous baseline enforcement and AI for the work that requires judgment, such as exploitability analysis and prioritisation.
Q: When does AI become the wrong tool for security decisions?
A: AI becomes the wrong tool when the decision must be identical every time, such as a build gate, compliance control, or regression check.
Q: What do security teams get wrong about AI-powered scanners?
A: They often treat probabilistic scanners as replacements for deterministic controls, when they are better thought of as a second layer.
Practitioner guidance
- Keep deterministic tools in the gating path Run rule-based scanners on every commit or pull request so known vulnerability classes are handled with consistent, auditable output before anything else is allowed to block a release.
- Use AI for triage, not primary enforcement Place reasoning models downstream of baseline scans so they can prioritise findings, assess exploitability, and reduce false positives without becoming the system of record for pass or fail decisions.
- Add reachability checks before model review Filter findings through reachability analysis, taint tracing, or dependency usage checks so AI evaluates only the issues that are actually exposed in the running application.
What's in the full article
Aikido's full blog post covers the operational detail this post intentionally leaves for the source:
- A side-by-side explanation of how SAST, DAST, and AI pentesting differ in cost, coverage, and speed.
- A walkthrough of Aikido's AutoTriage workflow, including reachability filtering before model review.
- Examples of complex findings such as IDORs, auth bypasses, and e-signature forgery that benefit from probabilistic reasoning.
- The implementation pattern for combining deterministic baseline scans with AI-assisted patch generation.
👉 Read Aikido's analysis of deterministic and AI-powered security tooling →
Deterministic security and AI triage: where each belongs in the pipeline?
Explore further
02/08/2026 1:05 pm
Determinism is still a governance control, not a legacy preference. Security tools need to produce stable results because teams use them to block deployments, prove remediation, and satisfy audit expectations. If identical code yields different outcomes, the control stops behaving like a control and starts behaving like noise. For IAM and NHI governance, that matters because access, secrets, and policy enforcement must be repeatable to be defensible.
A question worth separating out:
Q: What should teams do before trusting AI output on code findings?
A: Teams should narrow the problem with reachability analysis, taint flow checks, and context about how the application is actually used. That reduces hallucination-like overreach and keeps the model focused on evidence rather than guesses. The best AI results come from bounded inputs, not from scanning the entire codebase blindly.
👉 Read our full editorial: Deterministic security still matters as AI tools enter the pipeline
