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Code security

Endor Labs ✓

AI-powered application security that prioritizes real risks.

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Open Source AI Security Risk Prioritization
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Code Analysis Multi Language Support Vulnerability Remediation Code security
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Verdict

A quick read before you dig into the full page.

Best if
AI-powered application security that prioritizes real risks
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Dependency on custom rules
Pick this when
Prioritizes real risks

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Overview

AURI is an AI static application security testing (SAST) tool developed by Endor Labs. Acting as security intelligence for AI coding agents, AURI helps teams prioritize real risks, reduce noise and remediate vulnerabilities quickly.

It understands how code works and identifies what matters most to the organisation. The tool intelligently analyses code, triaging false positives and validating multi-file and multi-function data flows.

It assists in identifying complex vulnerabilities beyond traditional rule-based scanning, such as business logic and authentication flaws. AURI integrates directly into AI code editors to give developers and agents the tools to fix code before their first commit.

The software automatically triages findings by parsing syntax, tracing data flow, and reasoning about context and logic to present issues that genuinely matter.

It validates findings, providing transparent evidence and reasoning for every decision. The tool allows the addition of custom prompts and rules to align agent behaviour with an organization's security policies, priorities, and threat models.

Moreover, AURI can highlight complex logic flaws and other risks typically found in pentest reports and bug bounty programs without the need for rule creation or upkeep.

It provides reachable findings and delivers precise, explainable fixes for developers. Additionally, AURI offers smart fix suggestions that generate context-aware solutions aligned with your codebase for review.

It supports over 40 languages, including Java, Javascript, Python, C#, C/C++, Go, Kotlin, TypeScript, Ruby, Rust, JSX, PHP, Scala, Swift, Terraform, and more.

Endor Labs website

Access & connections

Where you can use Endor Labs.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • Code

Output

  • Code

Pros & cons

Pros

  • Prioritizes real risks
  • Reduces noise
  • Fast vulnerability remediation
  • Identifies organizational importance
  • Analyses multi-file data flows
  • Triages false positives
  • Detects complex vulnerabilities
  • Syntax parsing
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  • Data flow tracing
  • Logical reasoning capacity
  • Transparent evidence provision
  • Custom rules addition
  • Security policy alignment
  • Threat modeling
  • Identifies logical flaws
  • Pentest report analysis
  • Bug bounty compatibility
  • Intelligent fix suggestions
  • Supports 40+ languages
  • Generates context-aware solutions
  • Reachable findings
  • Delivers precise fixes
  • Explainable fixes
  • Customization of prompts
  • Vulnerability detection before commit
  • Manual research skipping
  • Auto-triage of findings
  • Scalable coverage for risks
  • Detects risky changes early
  • LLM security issue identification
  • High-signal finding focus
  • Guides on remediation
  • Verifiable trusted changes
  • Monitor severity and risk
  • Multi-file, multi-function analysis
  • Authentication guard understanding
  • Framework-specific sanitization
  • Reduced false positives
  • Add custom prompts
  • Java, Javascript, Python support
  • C#, C/C++, Go support
  • Kotlin, TypeScript, Ruby support
  • Rust, JSX, PHP support
  • Scala, Swift, Terraform support
  • Business logic flaws detection
  • Authentication flaws detection
  • Contextual analysis

Cons

  • Dependency on custom rules
  • No explicit mention of real-time support
  • No explicit mobile language support
  • No explicit built-in threat intelligence
  • No explicit support for older languages
  • May miss risks during auto-triage
  • No explicit hardware security integration
  • Dependent on code syntax parsing

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Releases 1

Initial release April 23, 2025 Current
Initial release of Endor Labs.

FAQ 12

What is Endor Labs AURI?
Endor Labs AURI is an AI-powered Static Application Security Testing (SAST) tool that provides security intelligence to AI coding agents. It aids teams in overseeing real risks, diminishing noise, and remediating vulnerabilities in a swift manner. AURI comprehends the functioning of code and distinguishes what is substantial for the organization.
How does AURI prioritize real risks?
AURI prioritizes real risks by intelligently analyzing code, differentiating false positives, and validating multi-file and multi-function data flows. It helps to determine complex vulnerabilities beyond conventional rule-based scanning. In addition, it provides reasoning for every decision and presents issues that genuinely matter after tracing data flow, parsing syntax, and reasoning about context and logic.
Can AURI validate multi-file and multi-function data flows?
Yes, AURI is designed to validate multi-file and multi-function data flows. It enables this through its intelligent code analysis feature that allows it to distinguish false positives and complete an extensive validation of data flows.
How does AURI reduce noise in the code?
AURI reduces noise in the code by automatically triaging findings. It does this by parsing syntax, tracing the data flow, and reasoning about context and logic to focus on actual issues that pose real risks and removing irrelevant or less important ones.
How does AURI understand how the code works?
AURI understands how code works by examining the relation between different parts of the code. This involves the analysis of syntax, tracing of data flow, and the reasoning about context and logic. It can also understand the security implications and vulnerabilities inherent in the code.
How does AURI remediate vulnerabilities quickly?
AURI remediates vulnerabilities quickly by integrating directly into AI code editors, providing developers with the tools to fix code even before the first commit. Additionally, it presents smart fix suggestions that generate context-aware solutions relevant to the codebase.
What type of vulnerabilities can AURI identify?
AURI can identify a wide range of vulnerabilities including, but not limited to, complex vulnerabilities beyond traditional rule-based scanning, business logic, and authentication flaws.
How does AURI integrate with AI code editors?
AURI integrates with AI code editors by being embedded directly within them. This provides developers and agents with the tools to fix code before making their first commit. The integration makes for a streamlined and efficient remediation process.
How does AURI validate its findings?
AURI validates its findings by providing clear evidence and reasoning for each decision. It parses syntax, traces data flow, and reasons about context and logic to validate the significance of its findings.
Can we add custom prompts and rules in AURI?
Yes, in AURI, users have the flexibility to add custom prompts and rules. This is valuable in aligning agent behaviour with the security policies, priorities, and threat models of an organization.
Can AURI align with an organization's security policies and threat models?
Indeed, AURI can align with an organization's security policies and threat models by allowing the addition of custom prompts and rules. This facilitates a uniformity between the tool function and the organization's defined security framework.
Does AURI provide fix suggestions?
Yes, AURI provides smart fix suggestions that generate context-aware solutions aligned with your codebase. These suggestions facilitate quick and effective remediation of identified vulnerabilities.
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