Model, data and system security assessments for chatbots, agents, RAG pipelines and LLM-powered products. We run AI red-teams, adversarial testing and TEVV so you can launch with confidence.
Use Case: Chatbots, customer-facing interactions.
RAG Leakage: Targeted extraction of confidential content from retrieval pipelines (vector stores, index chunks).
Prompt Jailbreaks / Injection: Structured jailbreak campaigns, indirect injections via user inputs, PDFs, or external websites.
Plugin & Connector Security: Key scope misconfigurations, insecure third-party connectors.
Context Manipulation & Prompt Chaining: Stateful attack chains exploiting hidden memory or multi-turn context.
Reputation Protection:
Avoid public PR disasters and viral leaks.
Misbehaving chatbots or data leaks can destroy brand trust overnight — we simulate real-world “viral risk” scenarios and fix them before users ever see them.
Data Leakage Prevention:
Ensure no internal, confidential, or personal data can be extracted via prompt-chains or model memory — even when an attacker scripts automated exploit attempts.
Financial Damage Mitigation:
Prevent exploitation that triggers unauthorized actions (transactions, approvals, account changes).
In fintech or trading environments, one successful prompt exploit can translate into direct financial loss or compliance fines.
Product Stability & User Trust:
Reduce hallucinations and unsafe responses — keeping customer experience, retention, and conversion KPIs stable.
CI/CD Integration: Through TEVV tests and automated prompt fuzzers, you get regression testing built into your sprints — less stress on launch day.
Quantifiable Metrics: Jailbreak success rate, leakage rate, hallucination delta → measurable KPIs for Product Management and QA.
Faster Mean Time to Remediate: We deliver reproducible exploit steps and actionable fixes, enabling your engineers to patch quickly.
Insurance & Compliance Leverage: Our structured reports shorten cyber insurance underwriting cycles and strengthen your risk documentation.
Prompt Injection Triggers Real Actions:
Security researchers showed how calendar entries, embedded files, or websites could trigger ChatGPT-like models to perform unauthorized actions — from reading local files to sending emails — purely via indirect prompt injection.
Copilot / Email Data Exfiltration (Red Team Demo):
Proof-of-concepts revealed that manipulated attachments could coerce LLM copilots into exfiltrating secrets via connected apps. Microsoft patched the issue after coordinated disclosure — the same class of exploit we replicate in our testing.
Use Case: Internal assistants, decision-support systems, process automation in finance, public sector, and energy.
Data Privacy Mapping: Identify where PII, trade secrets, and regulated data live inside your RAG indexes or model pipelines.
Access & Authorization Controls: Ensure only intended roles and tokens can query sensitive models.
Model Theft / Supply Chain Risk: Inspect containerized model images, checkpoints, and retriever pipelines for data exfiltration or IP exposure.
Audit & Forensic Readiness: Build traceable logs and provenance data to prove compliance during audits.
Audit-Ready Evidence:
Generate TEVV-based reports and metrics directly usable for compliance dossiers (NIS-2, DORA, ISO 27001) — reducing regulator friction.
Compliance Assurance:
Prevent unintentional data transfers to insecure cloud regions and provide technical evidence for DPOs and auditors.
Reduced Operational Risk:
Stop inside-out attacks (malicious employees or privilege abuse) through hardened access control and traceable activity.
Business Continuity:
Especially in energy and manufacturing sectors, we ensure LLM-based assistants cannot trigger false operational commands or propagate misinformation across control networks.
Forensic Readiness: Improved logging and telemetry enable faster incident response and help you meet insurance reporting timelines.
Supply Chain Hardening: Container and dependency audits reduce the risk of hidden backdoors or poisoned pre-trained models.
Proof of Remediation: Retest & regression evidence that satisfies auditors and internal QA.
RAG / Vector Store Extraction:
Multiple studies demonstrated that poorly secured retrieval pipelines allow reconstruction of private data from embeddings — even when sources were not publicly exposed.
Systemic Jailbreaks & Safety Failures:
Commercial models have been repeatedly bypassed to ignore content restrictions and produce sensitive or harmful content.
This risk intensifies when enterprises integrate plugins, agents, or autonomous decision layers.
What You Get
Executive Risk Brief: C-suite ready, risk-weighted summary.
Technical Red-Team Report: Reproducible prompts, PoC logs, impact scoring.
TEVV Metrics & Dashboard: Leakage, jailbreak, and hallucination data before/after fixes.
Sprint Testpack: Automated prompt fuzzers and regression tests for your CI pipeline.
Forensic & Audit Pack: Logging and provenance recommendations + Retest Certificate.
ROI Logic:
A single data leak, hallucination-driven failure, or unauthorized transaction can cost more than an entire testing engagement.
We quantify exposure vs. mitigation cost — making security a business case, not a compliance checkbox.
Book a Free Discovery Call — define scope in 48 hours, get a risk quick-scan scheduled within 72 hours.
Start with a Scoped TEVV + Red-Team (2–3 Weeks) — focus on high-impact zones (RAG, auth, plugins).
Integrate CI Testing & Monthly PTaaS — continuous validation embedded in your DevOps cycle.
🔹 Experienced OWASP Testers – we know the relevant standards inside out.
🔹 100% Remediation Rate – we don’t just find vulnerabilities; we help you fix them.
🔹 Regulatory Experts – GDPR, PCI DSS, and BSI-ready reporting.
🔹 Zero False Positives – every finding is manually validated by senior pentesters.