2.3 years → < 24 hours
Zero Day Clock · CSA AI Vulnerability StormThe AI Vulnerability Storm playbook was written by 70+ CISOs, including the security chiefs of Google, Cloudflare, Atlassian, the NFL, Sophos, and Rivian. They agree on one thing. Weaponization now happens at machine speed, and it's permanent.
The full playbook, free, no form. 29 pages on building a Mythos-ready program.
70+ CISOs ratified what comes next. A selection of contributors who shaped the playbook:
Affiliations listed for identification only. Inclusion does not constitute endorsement of Pixee.
What modern defense requires
The AI Vulnerability Storm paper calls for 11 priority actions.
Detection
Find what's exploitable
Resolution
Fix it at machine speed, with an audit trail
Foundation
Governance, inventory, segmentation
Pixee is how you respond to machine-speed offense
Pixee reduces risk by inserting security into the design and spec process. We then fix any vulnerabilities that still make it through to production.
Design on the left, defense on the right, one loop. Constantly improving context creates compounding security.
The proactive prong · before code
The AI is going to write the code. The only question is whether it knows what not to write before it starts.
Foresight is design-stage security, on the same context graph as VulnOps.
Ingests your PRDs, design docs, and tickets (Confluence, Notion, Google Docs, Jira, Linear) as they're written.
Pulls the security promises the design makes, explicit and implicit, and generates the misuse cases teams couldn't write at scale.
Pushes those promises into your tickets (DevRev, Linear, Jira) so engineering sees them at planning, not after launch.
When a PR lands, compares the code against the design's threat model and flags the drift between what shipped and what was promised.
A real example
A PRD promised user credentials would be hashed with bcrypt and exported PII encrypted at rest. The implementation hashed the credentials with MD5 and wrote the PII in plain text. Foresight caught the drift at PR review. The promise the design made is the contract the implementation has to keep.
Promises 2 explicit · 1 implicit
feat(export): customer data export endpoint
Checked against design promises:
credentials hashed with bcryptPII encrypted at restThe reactive prong · after detection
Pixee runs the four stages after detection — triage, fix generation, fix validation, PR creation. Our agents understand your code, your conventions, and your history, so you can wipe out vulnerabilities at machine speed.
Three layers of exploitability analysis hit every finding before a human does. Up to 95% drop as unreachable, unexposed, or already compensated. Your team only sees what an attacker could actually hit.
Read the Triage Automation PlaybookPixee reads your codebase first — the patterns you follow and the controls you already have in place — then generates a fix that fits. The change that lands looks like your team wrote it.
How Pixee fixes match your conventionsThe Fix Evaluation Agent is why 76% of Pixee fixes merge as-is. Three gates run before any PR opens: tests, conventions, and regression risk. Every drop, fix, and merge is logged as an auditable disposition.
Why 76% of Pixee fixes mergeFixes ship as ordinary pull requests, scoped to the lines they touch, with exploitability context inline. Your team reviews and merges in its normal flow.
How Pixee fits your existing review flow
The difference
One Context Graph powers both halves. Every fix VulnOps ships teaches Foresight what to watch at design time. Every promise Foresight tracks sharpens VulnOps downstream.
A private, per-customer model of your codebase, scanners, conventions, history, and architecture. Never shared, never used to train shared models. It's why triage reads exploitability right for your deployment, and why fixes look native to your code.
Three layers of exploitability triage filter out what isn't reachable, exposed, or actually exploitable.
Industry baselines for unsupervised AI fix merge sit in the 30–40% range. Both numbers are published and audited.*
Pixee unifies findings from 12 native scanners — CodeQL, Snyk (SAST + SCA), Semgrep, Checkmarx, Veracode, SonarQube, GitLab SAST, HCL AppScan, Synopsys Polaris, Aqua Trivy, DefectDojo, Datadog SAST. Anything else lands via universal SARIF v2.1.0. One view across first-party code, dependencies, and containers.
Every triage drop, fix regenerate, fix exit, and PR merge is written as an auditable disposition with its rationale. When an auditor or board asks "what did we do, and why?", the answer is already written, across your whole surface.
Pixee defines
The operating function that runs every step between detection and merge — triage, fix, validation, PR — at machine speed, with every decision logged. It's the Resolution layer of the CSA playbook (PA 11), and Pixee's reactive prong.
Pixee defines
The category for security software that acts on findings instead of just alerting on them. Detection tells you what's wrong; Agentic Security Engineering does something about it.
Three models: fully-managed Cloud (SaaS), self-hosted in your own VPC (Helm into existing Kubernetes, or a self-contained cluster), or fully air-gapped/offline for regulated environments. SaaS is SOC 2 Type II; self-hosted adds customer-managed encryption keys, private networking, and your choice of LLM (Azure OpenAI in your tenant, Databricks, or on-prem). Pixee is SCM-native — it connects to your existing scanners (native or SARIF) and repos through scoped API permissions, with no agents on developer machines and no build-system changes. First triaged findings land in hours, not weeks. Full deployment and compliance detail is on our compliance page.
The Fix Evaluation Agent runs three gates before a PR opens — that's how 76% of fixes merge as-is. Failed candidates are logged for your team's review, not silently dropped. Fixes that do ship are ordinary pull requests scoped to the fix footprint.
Pixee accesses your code through your SCM provider's API (GitHub, GitLab, Bitbucket) with scoped permissions. Code is processed in-memory for triage and fix generation; nothing is persisted to disk or shared infrastructure. Your per-customer Context Graph is never shared and never used to train shared models. Full security and compliance documentation is on our compliance page.
Pricing is outcome-based, calculated against your annual SAST + SCA scanner findings — not per developer, not per repository. Unlimited developers, no seat caps. Sizing comes out of the demo conversation. Current structure is at /pricing.
The next step
A live walkthrough with real examples from production deployments.
We map Pixee to your scanners and SCM, so the integration is clear up front.
You leave with the sizing math and a concrete integration plan.
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