Agentmetry vs Xalgorix: Which is Better in 2026?
A comprehensive comparison of Agentmetry and Xalgorix covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Agentmetry if:
- →You need a broader feature set (6 features vs 5)
- →You need records agent activity at the tool boundary or mitre att&ck technique tagging per event
Choose Xalgorix if:
- →You want more affordable paid plans (from $1/mo)
- →You need 22-phase methodology with an explicit exploit-verification phase or every reported finding carries a reproduced working exploit
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Agentmetry vs Xalgorix: At a Glance
Pricing Comparison: Agentmetry vs Xalgorix
Understanding the pricing differences between Agentmetry and Xalgorix is crucial for making the right choice. Here's how their plans compare side by side.
Agentmetry Pricing
Xalgorix Pricing
💡 Pricing takeaway: Both Agentmetry and Xalgorix offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from Agentmetry and Xalgorix stacks up.
What Makes Each Tool Unique
🔵 Unique to Agentmetry
Features available in Agentmetry but not in Xalgorix:
- ✓Records agent activity at the tool boundary
- ✓MITRE ATT&CK technique tagging per event
- ✓Sequence correlation into single critical alerts
- ✓Runs fully local with zero cloud calls
- ✓Secret values excluded from the trail
- ✓SIEM-readable output format
🟣 Unique to Xalgorix
Features available in Xalgorix but not in Agentmetry:
- ✓22-phase methodology with an explicit exploit-verification phase
- ✓Every reported finding carries a reproduced working exploit
- ✓GitHub Action fails the build only on proven findings at your severity threshold
- ✓Public REST API, signed scan.completed webhooks and an open-source CLI
- ✓Dated, evidence-backed branded PDF reports for auditors
Use Case Recommendations
Best for: Agentmetry
Agentmetry is a local flight recorder for AI coding agents, written for the security engineer who found out their company was running Cursor by reading a pull request. Endpoint detection sees a process; it does not see that an agent read a private SSH key and then made an outbound network call in the same session. Agentmetry records agent activity at the tool boundary — every read, shell command and fetch — correlates the sequence, tags it against MITRE ATT&CK technique IDs, and raises a single critical alert for the pattern rather than a stream of individually unremarkable events. The worked example on the homepage is exactly that: a `cat ~/.ssh/id_rsa` read tagged T1552.004, an `aws configure list` shell call tagged T1059 with DLP flagging an AWS access key, and a WebFetch to a paste site tagged T1071.001, correlated into one credential-exfil finding. Secret values themselves are never written to the trail. It runs entirely on the machine with zero cloud calls, ships nine detection rules in the current phase, and emits in a format existing SIEMs already read, so it slots into an established pipeline rather than becoming another console. Install is a git clone plus `pip install -e`, with a PowerShell installer for Windows. The whole thing is Apache-2.0 open source with the code public, which matters for a tool whose entire value proposition is that it watches privileged activity.
Ideal use cases:
- •Teams or individuals who need records agent activity at the tool boundary
- •Teams or individuals who need mitre att&ck technique tagging per event
- •Teams or individuals who need sequence correlation into single critical alerts
- •Teams or individuals who need runs fully local with zero cloud calls
- •Anyone focused on security workflows
- •Anyone focused on agents workflows
Best for: Xalgorix
Xalgorix is an autonomous penetration-testing agent whose distinguishing rule is that it reports nothing it has not exploited. Point it at a running application or a repository and it works through a twenty-two-phase methodology — reconnaissance, CORS and cookie handling, injection, IDOR, and on through to an explicit exploit-verification phase — and every finding that reaches the report has a working proof attached. That constraint is the answer to the failure mode that makes most automated scanners unusable in practice: a wall of maybe-vulnerabilities that a human has to triage before any of it can be acted on. The published example run is against pentest-ground.com, a deliberately vulnerable public target, and returned nine findings including remote code execution as root via an eval endpoint and a full database dump through auth bypass, in about seventeen minutes, with each exploit reproduced before it was written up. The CI story follows from the same rule: a GitHub Action runs an exploit-verified pass on every pull request and fails the build only on findings it actually proved, at a severity threshold you set, so the gate is on real risk rather than scanner noise. There is a public REST API, signed scan.completed webhooks and an open-source CLI, plus branded PDF reports that are dated and evidence-backed for auditors.
Ideal use cases:
- •Teams or individuals who need 22-phase methodology with an explicit exploit-verification phase
- •Teams or individuals who need every reported finding carries a reproduced working exploit
- •Teams or individuals who need github action fails the build only on proven findings at your severity threshold
- •Teams or individuals who need public rest api, signed scan.completed webhooks and an open-source cli
- •Anyone focused on pentesting workflows
- •Anyone focused on security workflows
🛡️ Other AI Security & Testing Tools to Consider
Agentmetry and Xalgorix aren't the only options. Here are other popular tools in the same space:
Lineation
Security control plane for AI agents — zero-trust agent identity, LLM and MCP gateways, policy-as-code, and prompt-injection defense
Axtary
Payload-bound authorization for AI agents — human approval is cryptographically tied to the exact action, so a changed payload is denied
Tracecat
Open-source SOAR for AI-native security teams — agents, cases, and workflows with human approval gates
Trestle
Local secret scanner with an MCP server so coding agents check their own output
ZeroLeaks
Continuous AI red teaming for agents, endpoints and MCP tools, with unlimited scans on every plan
Bot Butcher
LLM-based spam classification API for contact forms — a reCAPTCHA alternative with no visitor friction
Is one of these your tool?
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Frequently Asked Questions
Is Agentmetry better than Xalgorix?
It depends on your needs. Agentmetry offers 6 key features including Records agent activity at the tool boundary and MITRE ATT&CK technique tagging per event, while Xalgorix provides 5 features including 22-phase methodology with an explicit exploit-verification phase and Every reported finding carries a reproduced working exploit. Agentmetry uses a open-source model with a free tier, while Xalgorix is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is Agentmetry cheaper than Xalgorix?
Xalgorix is cheaper, starting at $1/month compared to Agentmetry's Apache-2.0 open source, installed from GitHub. No paid tier or pricing page is published as of August 2026.. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use Agentmetry and Xalgorix together?
Yes, many users combine Agentmetry and Xalgorix in their workflow. Agentmetry excels at records agent activity at the tool boundary, while Xalgorix shines with 22-phase methodology with an explicit exploit-verification phase. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between Agentmetry and Xalgorix?
While both are ai security & testing tools, Agentmetry emphasizes records agent activity at the tool boundary, whereas Xalgorix is known for 22-phase methodology with an explicit exploit-verification phase. The best choice depends on your specific workflow and feature priorities.
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