Buying and running it · Lesson 8 of 10
How AI code security tools prioritize findings
ANSWER FIRST
More code means more findings, and a team can only fix some of them this week. Tools rank findings in five main ways: whether the vulnerable code is reachable, whether it is exploitable, how exposed and important the application is, whether several scanners reported the same issue, and whether a model judges it a false positive.
Editorial assessment · Compiled from vendor product, docs, pricing and marketplace pages · Rated October 2026
By Best AI Code Security reviewers · 10 June 2026 · 3 min read
Why does prioritization matter more with coding agents?
Assistants and agents raise the volume of code that reaches pull requests, and every new dependency brings its own known vulnerabilities. A queue that grows faster than a team can work it stops being useful. Prioritization is how a tool decides which items reach the top, and it carries 10% of our score as prioritization and context.
What are the main methods?
- Reachability. A vulnerability in a dependency only matters if the application calls the vulnerable code. Reachability analysis checks that, so unreachable findings can be deprioritized. Endor Labs builds its product on reachability across dependencies, containers and first-party code.
Source: Endor Labs · Reviewed Sep 2026
- Exploitability checks. A tool can test whether a specific vulnerability can be triggered. Cycode's AI Exploitability Agent confirms whether a CVE is reachable, and OX Security's Agentic Pentester ties exploitable issues back to code and APIs.
Source: Cycode · Reviewed Sep 2026
Source: OX Security · Reviewed Sep 2026
- Business and exposure context. The same finding matters more in an internet-facing payment service than in an internal tool. Legit Security's risk scoring weighs business criticality, compliance, GenAI use, APIs and internet exposure, and Apiiro connects code to runtime context through its Software Architecture Graph and Risk Graph.
Source: Legit Security: ASPM platform · Reviewed Sep 2026
Source: Apiiro · Reviewed Sep 2026
- De-duplication. Teams that run several scanners see the same issue more than once. ASPM platforms correlate findings; Legit pulls findings from existing scanners into one de-duplicated queue.
Source: Legit Security: ASPM platform · Reviewed Sep 2026
- Auto-triage. Some tools use a model to mark likely false positives. Semgrep Assistant auto-triages findings and uses code context to cut false positives.
Source: Semgrep · Reviewed Sep 2026
Which method should a team start with?
It depends on where the noise comes from. If most findings are in dependencies, reachability removes the largest share. If the problem is several scanners reporting the same thing, de-duplication in an ASPM platform comes first. If the team cannot tell which applications matter, business context helps most. The methods combine, and several vendors describe more than one.
When evaluating a tool, ask to see one real finding with the evidence behind its rank: the call path for reachability, the test for exploitability, or the context fields for business risk.
Ranking also decides what an automated fix agent works on first. Pointed at an unranked queue, a fix agent spends its effort in the order findings arrived; pointed at a ranked one, it starts with what is reachable and exposed. Our note on agentic remediation compares the fix agents vendors describe.
How do the tools we score compare?
On prioritization and context, Endor Labs and Apiiro lead at 5.0. Snyk and Aikido Security score 3.5 because the pages we reviewed do not describe the method.