The AI Race Against Time
More vulnerabilities, discovered faster, exploited sooner.
Global CVE explosion
72,812
CVEs published in 2026 through September, already 51% more than all of 2025
Shrinking time to exploitation
−7 days
Mean time to exploit in 2025: attacks now start, on average, before a patch is released
What the CRA Expects
Manufacturers must notify ENISA and their national CSIRT in three stages, starting just 24 hours after becoming aware of an exploited vulnerability.
24h
Early Warning
First alert, with a suspected cause and the countries affected
72h
Notification
Details of the vulnerability, affected products and mitigations taken
14d
Final Report
Within 14 days of a fix being available, with severity, impact and the corrective measure
Ready to Report In 24 Hours?
To meet each deadline, you need answers fast:
- Are these real vulnerabilities, not just potential weaknesses?
- Are they reachable and exploitable in your product?
- Is a verified fix available, or can one be generated quickly?
The CRA Vulnerability Management Gap
The CRA makes you responsible for every vulnerability in your product, whether it’s in your own code, a third-party component or an open-source library. The obligations are fixed in law, while the workload behind them keeps growing.
More Code, Faster Releases
AI-driven development means more code, more dependencies and shorter release cycles. Every release brings new first-party, third-party and open-source components, and new chances for gaps.
Hard to Prioritize
Without exploitability evidence, severity scores alone drive the queue. Teams spend effort on noise while real risk waits.
No Proof of Risk
Scanners flag thousands of findings, but rarely show whether a vulnerability is reachable, exploitable and relevant in your product.
Thin Audit Trail
Internal code and external components are often managed in separate workflows, with decisions scattered across tickets, chats and spreadsheets. Assembling traceable, audit-ready evidence within 24 or 72 hours is close to impossible.
AI-enabled Vulnerability Remediation, Built into Your Development Cycle
Keysight AI Analysis for CRA is an AI-driven code analysis service with vulnerability management that automates the entire vulnerability life cycle. Built on Keysight's security expertise, our proprietary AI-powered framework identifies vulnerabilities, tests whether they can be exploited, suggests and validates fixes, and documents every step.
Key Capabilities
Intelligent Triage
Triages SBOM-based CVEs and SAST findings, filters out false positives and ranks exploitable risks first.
Verified Fixes
Builds, tests and validates every fix in a sandbox to confirm the vulnerability is resolved.
Reachability Analysis
Shows which vulnerabilities can actually be reached and exploited from real production entry points.
CRA Evidence
Creates traceable, audit-ready records for vulnerability handling, coordinated disclosure, incident reporting and conformity assessment.
- Onboarding
- Initial Assessment
- AI Analysis and Validation
- Results Review
- Retrospective
Onboarding
You share access to your source code repository and environment details. Because we analyze source code, not binaries, every finding points to the exact line, and fixes arrive as ready-to-merge patches.
Initial Assessment
Keysight assesses the prerequisites and resolves blockers with you before the full analysis.
AI Analysis and Validation
Our framework collects SCA data and runs AI-driven SAST, then spins up a sandbox to test reachability and exploitability and to verify each patch.
Results Review
Your team and Keysight review findings, patch results and remediation recommendations together.
Retrospective
We identify coverage gaps and capture feedback for future improvements.
All options cover first-party, third-party and open-source code in one unified AI workflow, with CI/CD pipeline integration coming soon.
Your IP Stays Yours
Your source code is your most valuable asset. We treat it that way.
- Host projects on offline AI servers, with no data sent to the cloud
- Choose AI models to match regional compliance
- Option to run on AI cloud service providers
- No training on customer data
Frequently Asked Questions
Reporting of actively exploited vulnerabilities and severe incidents applies from 11 September 2026. The remaining requirements, including vulnerability handling and SBOMs, apply from 11 December 2027.
No. The AI suggests patches and verifies them in a sandbox. Critical patches always go through human review before they reach your codebase.
No. Projects can run on offline AI servers, and your data is never used to train models.
You already know which vulnerabilities are reachable and exploitable in your product, and every finding has a traceable record. When a new exploited vulnerability appears, you can assess impact quickly and report with evidence.
Findings flow into your existing workflow, for example as prioritized Jira tickets or sprint items.
With a proof of concept on one of your own products. It follows the five steps above and ends with a retrospective on results.