deepsec
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Deepsec is a security harness for finding vulnerabilities in your codebase powered by coding agents
pnpm deepsec --model-auth local ai: mode: local provider: local
Summary
deepsec is an open-source vulnerability scanner that uses AI agents to review large codebases for security issues that have sat undetected for a long time. It runs as a command-line tool: npx deepsec init walks you through picking a model and a payment method (your own API key or Vercel AI Gateway), then scans unattended, resuming automatically if interrupted, with --max-cost-usd and --max-duration flags to cap spend on runs that can otherwise reach thousands of dollars. It's aimed at application security teams and developers doing on-demand review of existing large-scale repos rather than continuous CI linting. It sits in the AI-driven code-review space, distinct from pattern-based static analyzers, fanning work out across worker machines for scale. First committed in 2026, it already has 9 contributors and 175 commits in the past year, suggesting active development.
Deepsec is a security harness for finding vulnerabilities in your codebase powered by coding agents
How deepsec helps
Which vulnerabilities in this codebase have been sitting undetected because no linter pattern catches them?
fans an AI review across every file in the repository at maximum reasoning depth, surfacing issues that pattern-based scanners are not built to see
Which parts of this application are actually reachable by an attacker versus just internal plumbing?
classifies each entry point by kind — endpoint, queue, cron, command line, webhook, agent tool — and by exposure, so findings can be weighed against how the code is actually reached
Did the last code review run get cut off before finishing, and does it need to start over?
tracks which files were already analyzed and resumes from there on the next run, so an interrupted scan never starts from the beginning
Is a finding from this scan the same one flagged last time, or something new?
assigns each finding a stable identity derived from its project, path, and title, so re-running the review recognizes repeat findings instead of duplicating them
Which of the flagged issues are worth a developer's time versus likely noise?
runs a revalidation pass that re-checks prior verdicts and reconciles them against the new scan, cutting the false-positive rate before anything reaches a report
How much is a review of this repository going to cost before it runs unattended for hours?
lets a run be capped by spend or by wall-clock time up front, since scans at maximum thinking levels can otherwise reach thousands of dollars on a large codebase
Languages
Command line
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Values are placeholders taken from each option’s declared default. Nothing is executed here — the output shown is a recording of a run that already happened.
Score card
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Shipping velocity releases a month, last 12 months
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Documentation quality release-notes rubric, 0–100
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Breaking-change discipline how rarely a release breaks users, and notice given
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Maintenance risk quiet time against its own cadence, maintainers
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Innovation & surface new capabilities, API and MCP surface
- Community health
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Contributor trend distinct committers, this year against last
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Maintainer concentration bus factor now against a year ago
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Issue backlog trend issues closed per issue opened, 12 months
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Responsiveness median time to a maintainer’s first reply
Nine scores for deepsec, each built from the releases, notes and API history this site tracks — and, on Researcher and Business, where it stands among every measured tool in its category and how that has moved.
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Blank means never measured; nothing here is a filled-in zero.
Peer standings are included with Researcher and Business. See how this tool ranks against its competitors, using data we don't publish anywhere else.
See plans →Each score is 0–100 on a published rubric, derived from data this site already shows. A dimension we cannot measure says so — it is never scored 0 and never enters a rank.
How this is scored
- Shipping velocity — releases a month over the last 12 months, on a log scale where 16 a month scores 100. Needs 3 releases in the window.
- Documentation quality — the release-notes rubric published on the analytics page, unchanged.
- Breaking-change discipline — the share of releases carrying a breaking change (none scores 100, half or more scores 0). Only projects that label breaking changes are measured: a clean record cannot be told from an unlabelled one.
- Maintenance risk — quiet time measured against the tool's own release cadence (quiet longer than 90 days and three typical gaps scores 0), plus the number of active maintainers and whether contributors are growing, where known. Higher is lower risk.
- Innovation & surface — new capabilities in the feature ledger this year, API and MCP operations added, and the share of commits that are features: the mean of whichever we hold.
- Community health (open-source tools only) — each is a direction, not a size: contributors this year against last, the bus factor now against a year ago, and issues closed per issue opened, where steady scores 50, doubled 100 and halved 0; plus the median time to a maintainer's first reply (an hour scores about 100, a month or more 0). A commercial card has no repository and carries none of the four.
- Documented delivery (commercial tools) — when a vendor's documented new capabilities have slowed against its own baseline, that counts against the overall standing as heavily as two low dimensions. Steady delivery, or too little history to judge, leaves the standing alone; it is never a sixth score.
- Open-source tools are scored on repository signals; commercial tools on their published changelog. Ranks compare tools within one category and one profile and need at least five measured peers; the overall standing needs three ranked dimensions. Best-in-breed or consolidator is a shape, not a quality, and is never scored.
Release-note detail over time
See how much detail deepsec puts in its release notes, quarter by quarter, and compare it with tracked tools in the same category. This history uses up to ten retained, reviewed notes per tool; sparse or blank older quarters may reflect that limit.
Checking release-note history…
Releases
3 entries
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- August 20263
Project health
Issue, contributor and maintainer activity in vercel-labs/deepsec, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.
- Contributors 10 +10 vs prior 12 months
- Maintainers 2 +2 joined · −0 left, last 12 months
- Bus factor 1 committers behind half the commits
- Community-filed 100% of issues opened, last 12 months
- Median time to close < 1 day first maintainer reply 5.9 hours
- Open backlog 23 of 35 issues ever filed
- Issues opened / month 0 · 0 communitymaintainers
- Open backlog 23
- Contributors / month 2
- Commits / month 3
- Stars 8,001
- bugs 37%
- features 17%
- other 46%
Counts from the project's public repository and git history; no individuals are identified. Maintainers are the committers covering 80% of the last year's commits. how we measure this
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