AI Penetration Testing to Identify and Reduce Model Exploits
Secure your AI and Machine Learning models - uncover hidden vulnerabilities before hackers strike
Why AI Penetration Testing Matters
Prompt injection, model theft, training-time poisoning, over-privileged tools, and privacy failures create unique AI risks that lead to data leaks, fraud, and legal exposure
Prompt injection and jailbreaks
Model theft and capability cloning
Training-time poisoning and backdoors
Over-privileged tools and agents
Privacy and governance failures
Software Secured’s AI Pentesting
Manual, hacker-led testing uncovering prompt injection, data leakage, model manipulation, and insecure integrations - validating how your AI systems handle real adversarial inputs and protect sensitive data
AI threat modeling
Map model boundaries, agent permissions, identities, and data stores to define material loss scenarios
- Quantify exploitability into business risk
- Prioritize defenses by material loss scenarios
Jailbreak and prompt-injection testing
Combine curated and generative attacks against prompts and RAG/vector stores
- Expose guardrail gaps with reproducible attacks
- Deliver prompts and outputs for engineers
Tool-use and agent workflow abuse
Exercise least-privilege, approval gates, and connector isolation across databases, payments, and cloud ops
- Validate least-privilege and approval efficacy
- Demonstrate realistic cloud and payment compromises
Model and data confidentiality probes
Test for training-data leakage, membership inference, and PII exposure
- Detect training-data leakage and membership risks
- Confirm redaction and vault protections
Abuse resilience and recovery
Assess how systems withstand and recover from misuse through controlled stress and fault injection
- Simulate abuse to test rate limits
- Check moderation and bypass defenses
What sets Software Secured Apart
Concrete loss modeling
We model data leakage, fraud, and unsafe tool actions, then estimate financial impact and prioritize fixes
- Quantify potential financial loss scenarios
- Focus remediation on measurable business risk
Standards-aligned AI test plans
Derived from Mitre AI ATLAS Matrix, Google SAIF Risks, OWASP Top 10 ML
- Map findings to leading compliance frameworks
- Ensure AI coverage meets global standards
Shareable, redacted Portal reports
Role-based views and one-click redacted reports protect sensitive details while tracking remediation
- Enable secure sharing with auditors and buyers
- Track remediation progress across all teams
Experienced pentesters
Full-time certified specialists perform tests and join reviews; no contractors
- Maintain consistency with expert-led testing
- Provide direct guidance through remediation cycles
What Our Clients Say
Trusted by Technology Leaders Protecting AI Systems
"Software Secured made this process seamless, helping us identify and remediate vulnerabilities efficiently, which in turn allowed us to focus on delivering value to our customers."
high growth startups, scaleups and SMB trust Software Secured
"Their team delivered on time and was quick to respond to any questions."
Trusted by high-growth SaaS firms doing big business
Transparent Pricing for Scalable Application Security
Security Made Easy
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Best Combined With
Combine AI Pentesting with Web App Pentesting
Our AI Penetration Testing Process
We make it easy to start. Our team handles the heavy lifting so you can focus on keeping your attack surface protected without the headaches.
Consultation Meeting. Our consultants span five time zones. Meetings booked within 3 days.
Customized Quote. Pricing tailored to product scope and compliance needs. Quotes delivered within 48 hours.
Pentest Scheduling. Testing aligned to your release calendar. Scheduling within 3-6 weeks - sometimes sooner.
Onboarding. Know what to expect thanks to Portal and automated Slack notifications. Onboarding within 24-48 hours.
Pentest Execution. Seamless kickoff, and minimal disruption during active testing. Report within 48-72 hours of pentest completion.
Support & Retesting. Request retesting within 6 months of report delivery. Auto-scheduled within 2 weeks.
“I was impressed at how thorough the test plan was, and how "deep" some of the issues were that their testing uncovered. Also, the onboarding process was simple and painless: they were able to articulate exactly what they needed from us, and showed a clear understanding of the product they would be testing during our initial demo”.
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Frequently Asked Questions
Get answers to common questions about AI penetration testing and how Software Secured supports your AI security goals.
What AI systems do you test?
LLMs, fine-tuned models, RAG pipelines, agents, and tool ecosystems across cloud/on-prem. We assess prompts, embeddings, vector databases, plugins, and the surrounding identity and data layers.
Do you need training data access?
Not always. We detect leakage via black-box prompts and logs. When available, we review datasets/redaction pipelines to evaluate membership inference, lineage, and sensitive data handling.
How does this help compliance?
Findings map to popular compliance frameworks. Evidence packages reduce audit findings, shorten cycles, and satisfy AI-specific security questionnaires.
What makes AI penetration testing different from traditional pentesting?
AI pentesting focuses on risks unique to models and pipelines, such as prompt injection, model poisoning, data leakage. In addition to testing common risk such as authentication, authorization, SQL injection and cross-site scripting.
Which regulations or compliance frameworks require AI pentesting?
While few explicitly mandate it today, frameworks like GDPR, HIPAA, SOC 2, ISO 27001, and the upcoming EU AI Act all expect technical safeguards with evidence-pentesting is the strongest proof.
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