Quick Answer
The best AI-built app audit services combine four things: a documented method for reviewing AI-generated code, security testing that covers access control and exposed secrets, coverage of any language-model features in the app, and a written report with a prioritized fix list. Dev Technosys heads the list below with a five-stage AI-built app audit, ISO 27001:2022 and ISO 9001:2015 certifications and a CMMI Level 3 appraisal. Eight more firms follow, and each entry says where the public evidence is thin.
What Should an AI-Built App Audit Cover?
AI coding tools produce working software quickly, but working is not the same as safe. Veracode’s 2026 GenAI Code Security Report, published July 28, found that AI models pass about 56% of its security tests on average, roughly flat against the year before. A useful audit therefore covers more than a code skim:
- Code and architecture: structure, error handling, maintainability and the parts of the design nobody asked the AI to think about.
- Access control and secrets: who can read or change which record, and whether any key ships to the browser or sits in the repository.
- Database rules: row-level security or equivalent rules on every table, tested with real accounts.
- Dependencies: whether each package exists and is the one intended. A USENIX Security 2025 paper found hallucinated package names in at least 5.2% of outputs from commercial models and 21.7% from open-source models.
- Language-model features: prompt injection, sensitive information disclosure, excessive agency and unbounded consumption, as named in the OWASP Top 10 for LLM Applications (2025).
- Report: findings with severity, reproduction steps and a retest.
If the app also touches wallets, tokens or smart contracts, ask for a separate smart contract audit. A general application audit does not replace one.
How Do You Compare Audit Providers?
- Ask for a sample report. A real report shows severity ratings, evidence and fix guidance, and not just a list of tool output.
- Get the scope in writing. Check whether it includes the database, the cloud settings, the language-model features and third-party services.
- Ask who does the work. Find out whether named engineers will review the code or whether a scanner will run unattended.
- Look for an AI-specific method. A provider that has thought about generated code will talk about hallucinated dependencies, default settings and over-permissioned AI features.
- Agree on a retest. A fix is only a fix once someone has checked it.
Which AI-Built App Audit Services Are Worth Shortlisting?
Figures below come from each company’s own website and are self-reported, so confirm them directly before signing anything.
1. Dev Technosys
- Founded: 2010
- Team Size: 250+
- HQ: Jaipur, India
- ISO 27001:2022 certified, ISO 9001:2015 certified and CMMI Level 3 appraised
- Five-stage AI-built app audit: discovery, code and architecture audit, AI functionality and data audit, security and risk audit, and a report with a prioritized remediation roadmap
- Compliance review that references the OWASP Top 10 for LLM Applications, GDPR and HIPAA
- Core Services: AI-built app audit, AI code audit, LLM integration review, AI app rescue, application security assessment
Dev Technosys leads this list because its audit follows the method described above end to end: it reviews generated code, APIs and database schema, examines the model, prompts and data, runs the security and risk checks and finishes with a report that ranks findings by risk and lists what to fix first. For a team that needs one provider to cover code, data and AI behavior, that scope is the practical advantage.
Best For: Teams with an AI-built app that need an independent, end-to-end audit and a ranked remediation plan.
2. a1qa
a1qa, a quality assurance firm with offices in Decatur, Georgia and London, says it has operated since 2003 and cites 1,100+ QA specialists. Its AI-generated code audit page promises an independent assessment of AI-built and vibe-coded software, looking at hallucinated dependencies, insecure patterns, architectural drift and gaps in test coverage, and it delivers a readiness verdict with a prioritized roadmap. ISO 9001, 27001 and 14001 badges appear on its site. a1qa suits engineering leaders who want a QA-style readiness verdict before release.
3. Hicron Software
Hicron Software says it was founded in 2006 and cites 380+ consultants, with offices in Poland, Spain, Germany and Switzerland. Its code review and audit services include an AI code review designed for human-written and AI-generated code, alongside independent source-code audits and security-gap audits. The page does not name specific certifications. Hicron suits mid-size businesses that rely on a business-critical application and want an independent audit without caring who or what wrote the code.
4. Apriorit
Apriorit, a software engineering firm with a Lynn, Massachusetts address on its site, says it was founded in 2002 and employs 400+ people. Its code audit scope includes code review, architecture analysis, DevSecOps pipeline review, threat modeling, dependency scanning and cryptographic controls, and it references OWASP, CIS and FIPS. ISO 27001 and ISO 9001 badges appear on the site. Apriorit suits technology and cybersecurity-product companies that want a deep, engineering-led audit of a custom codebase.
5. Packetlabs
Packetlabs, a penetration testing firm headquartered in Toronto with offices in San Francisco and Sydney, offers AI and LLM penetration testing that covers prompt injection, retrieval-augmented generation, agents and plugin or API abuse, based on the OWASP Top 10 for LLM Applications. Its site calls the firm CREST-certified and SOC 2 Type II-attested, and it displays a CREST AI signatory logo, all of which are self-reported. Packetlabs suits companies shipping chatbots, copilots or other language-model features that need adversarial testing.
6. Secarma
Secarma, a UK cybersecurity firm with a registered office in Manchester, says it has operated for more than 20 years. Its LLM application security testing maps findings to OWASP’s LLM list, CWE and MITRE ATLAS, and it offers separate tests for AI agents, chatbots and AI integrations. CREST, ISO 27001, ISO 9001 and NCSC Assured Service Provider logos appear on the page and are self-reported. Secarma suits UK and European businesses building on hosted or local language models.
7. Bridewell
Bridewell, a UK cybersecurity and compliance firm that says it was founded in 2013, offers AI and LLM penetration testing covering prompt injection, data leakage, adversarial input and API or integration testing. Its site says the firm is certified to ISO 27001, ISO 27701 and ISO 9001, and that its security operations center holds accreditations that include SOC 2. These are self-reported. Bridewell suits regulated or enterprise-facing companies in the UK and US that are putting language-model features into production.
8. Trail of Bits
Trail of Bits, a security research firm that says it was founded in 2012, lists software assurance services whose deliverables include reports, exploit proofs of concept, CI-ready Semgrep and CodeQL rules and fuzzing harnesses. Its site cites 656 audits and 988 publications, and it lists AI and machine-learning security as a practice. Trail of Bits suits teams with security-critical code, including smart contracts and AI systems, that want research-grade review and detection rules they can keep running.
9. Bishop Fox
Bishop Fox, an offensive security firm that says it has operated for almost two decades, publishes an AI and ML security assessment that covers the model, application, agent and infrastructure layers and maps to the OWASP LLM, ML and agentic Top 10 lists and to MITRE ATLAS. It also lists AI-powered application penetration testing and secure code review. Bishop Fox suits funded product companies that want deep manual testing of AI features and agents.
Red Flags That Suggest an Audit Is Not Worth Paying For
- A scanner report presented as an audit, with no manual review of access control.
- No mention of language-model features when the app has them.
- A fixed price and date quoted before anyone has seen the app.
- No retest after fixes.
Frequently Asked Questions
What is an AI-built app audit?
It is an independent review of an app that was built with AI coding tools or that uses AI components. It checks the code and architecture, security and data exposure, language-model behavior and cost controls, and ends with a ranked list of fixes.
How much does an AI-built app audit cost?
Cost depends on the size of the app, the number of integrations and the depth of testing, so ask each provider for a written scope and quote. Treat any price quoted without seeing the app with caution.
Do I need a smart contract audit as well?
If the app deploys or interacts with smart contracts, yes. An application audit looks at the app around the contract, while a smart contract audit examines the contract logic itself, and the two answer different questions.