AI is uncovering vulnerabilities faster than ever, and attackers use AI to weaponize them, often within a day. A backlog is no longer a place risk can wait. Heeler runs AppSec as one automated loop and brings your team in only where a decision needs a person.
AI is helping uncover vulnerabilities faster than ever, and attackers use AI to weaponize them. CVE disclosures are on pace for a record of about 74,000 this year, and the median time to exploitation is now a day. The people who can triage and fix by hand stay the same. That is the vulnpocalypse.
vulnerabilities published in the first half of 2026, compared with the first half of 2025
of exploited CVEs were exploited before, on or within seven days of disclosure
for a frontier AI model to turn known vulnerabilities into working exploits, with no human involved
of breaches happened when a patch was already available
Stop new risk where it starts: in the agent, at the commit and on the pull request.
Every finding ranked the moment it lands, from what runs and what it reaches. Same inputs, same answer.
The fix version is calculated, not guessed. An agent makes the change, validates it in your CI and repairs what breaks. Your team merges it.
Each one runs end to end without a triage meeting. Pick one.
CVE-2022-22965 in spring-beans, on checkout-api
Tier 1, production, internet accessible, function reachable
Urgent. The SLO is 14 days.
CODEOWNERS names @payments-team
Ticket in PAY, message in #payments-security
Auto-fix opens the upgrade PR, validated in CI
Add PDF export to billing-service
Heeler MCP tells the agent your guardrails: licenses, minimum package age, known vulnerable versions
The agent picks a version that passes, not the newest one
The sensor records prompts, tool calls and skills as the agent works
The CLI hook checks secrets and packages, and the session is linked to the commit
PR Guardrails check new dependencies, secrets and agent files
Malicious-package intelligence reports the bad version as soon as it is known
A minimum package age rule was already holding brand-new versions back
PR Guardrails block any pull request that adds the malicious version
Every repository and running service with it, at the exact version, even when unpinned, from what runs
Security is alerted and each owning team gets a ticket
Auto-fix opens a pull request to a safe version, validated in your CI
The CLI hook checks the key with its provider before the commit exists. It is live
The agent is told to remove the key and rotate it. Nothing reaches the repository
A key already in the change is exposed, so PR Guardrails alert the reviewer that it must be rotated
Keys on any branch or in git history are found and proven live against the provider
Rotate now. Ticket to the team that owns the repository, alert to security
A finding is days from its SLO due date
Heeler messages the owning team before the deadline passes
Past due, PR Guardrails block new pull requests in that repository
The fix PR passes, because it removes the vulnerable version. Merge it and the block lifts
Cannot fix yet? Record a reason and an end date. When it ends, the finding comes back
AI coding means more code, AI attackers mean less time, and together they add up to more findings than any team can work by hand. Every part of the platform answers one of the three.
Agents get your policy while they write, commits are checked before they exist, and every pull request is checked before merge.
Every agent file is scored from 0 to 100, changes to them are guarded, and the sensor shows what each session did.
Each finding is ranked the moment it lands, from what runs, what it reaches and how critical the service is.
SLOs you set, reminders before they lapse, and every exception kept with a reason, an owner and an end date. SBOMs when you ask.
Upgrade and code fixes arrive as pull requests, validated in your CI and repaired when the build fails.
Work goes to the right team, in its own tools, without a triage queue.
Code, cloud, agents, owners, business and threat intel in one Context Engine. Prevent, Fix and Operate all read it.
See the Context Engine →Rankings, fix versions, guardrail results and owners are decided by rules, not by an LLM. AI writes and repairs code where it helps.
See how Autotriage decides →Work lands in each team's own tickets and channels, on the timeframes you set. Nothing to add to your pipelines.
See setup →