Researching how modern systems fail under real attack pressure.
ShabuShabu Security combines penetration testing, vulnerability research and AI security analysis to study the attack paths emerging across web applications, APIs, autonomous AI systems and complex digital products.
Attack surfaces are evolving faster than traditional checklists.
Security research helps us understand weaknesses that do not fit neatly into a single known vulnerability category. Modern products combine users, data, APIs, automation, AI models and external services into one connected system.
Our research focuses on the points where these components create new trust assumptions and where several individually limited weaknesses can combine into a meaningful attack path.
Discover emerging attack patterns
Study security failures created by new architectures, application behavior and connected services.
Validate practical impact
Separate theoretical weaknesses from issues that can produce meaningful security consequences.
Improve defensive testing
Turn research knowledge into stronger penetration testing methodology and better remediation guidance.
The security disciplines shaping our research.
ShabuShabu research focuses on modern attack surfaces where technical vulnerabilities interact with permissions, product logic and increasingly autonomous systems.
Web Application Security
Research into authentication, authorization, business logic, sensitive workflows and multi-step web application attack scenarios.
AI & LLM Security
Study of prompt-based manipulation, model-connected tools, AI agents, data access and emerging permission boundaries.
API Security
Research around object authorization, interface trust, data exposure and API-driven application attack paths.
Business Logic Vulnerabilities
Analysis of cases where legitimate application features can be combined into unintended security outcomes.
Autonomous Agent Security
Research into how AI-controlled tools and workflows change traditional assumptions around authorization and execution.
Attack-Chain Analysis
Understanding how multiple individually limited weaknesses can combine into higher-impact compromise paths.
Anthropic Mythos and the changing model of vulnerability research.
Frontier AI systems are changing the speed and scale at which software can be analyzed for security weaknesses. Our research tracks how Mythos-class cybersecurity capabilities affect vulnerability discovery, exploit analysis and defensive testing.
For ShabuShabu Security, the important question is how these capabilities can strengthen defenders while remaining inside responsible research, authorization and disclosure boundaries.
Security research is valuable when it improves defense.
We do not measure research quality by the number of automated findings produced. Meaningful security work requires context, validation and a clear path to remediation.
New Attack Paths
Identifying previously overlooked ways in which application components or permissions interact.
Validated Impact
Confirming whether a suspected weakness can produce meaningful security consequences.
Better Testing Methods
Translating research insights into stronger penetration-testing workflows and assessment logic.
Responsible Disclosure
Handling validated findings through controlled channels designed to support remediation.
Engineering Insight
Helping teams understand why a security boundary failed rather than only documenting the symptom.
Verified Remediation
Confirming that security fixes actually remove the identified attack path.
From observation to defensible security finding.
Research is structured around controlled validation rather than unsupported assumptions about potential impact.
Observe
Identify unexpected behavior, weak trust assumptions or security boundaries worth deeper investigation.
OBSERVE / MODEL / HYPOTHESIS
Test
Assess the hypothesis inside an authorized, controlled environment using appropriate testing methods.
TEST / REPRODUCE / ANALYZE
Validate
Determine whether the behavior creates realistic security impact and identify the actual root cause.
IMPACT / ROOT CAUSE / EVIDENCE
Remediate
Communicate the issue responsibly and support a path toward reducing or removing the underlying risk.
DISCLOSE / FIX / VERIFY
Capability matters. So do the boundaries around it.
Offensive-security research can involve sensitive technical information. ShabuShabu Security approaches research with defined authorization, controlled validation and responsible handling of findings.
Turn offensive-security research into stronger product defenses.
If your application includes complex authorization, high-value workflows, public APIs or AI capabilities, ShabuShabu Security can assess where new attack paths may emerge before they become operational risk.