Black Duck • Application security
Seeker Interactive is the IAST platform that instruments running applications via agents during functional and automated testing. Patented active verification automatically retests findings to confirm exploitability. Sensitive-data tracking traces data flow at runtime. Real-time vulnerability detection runs inside QA cycles rather than as a separate scan.
Merito sells Seeker Interactive and operates the agent deployment, sensitive-data baseline, active verification tuning, and CI/CD integration that turn the platform into reliable IAST coverage inside the customer's QA program.
What it is
Seeker Interactive is Black Duck's IAST platform. Agents instrument running applications and analyze application interactions in real time during manual tests, automated tests, or any combination of both. The architecture surfaces vulnerabilities while the application is exercised, which closes the gap that pure SAST and DAST cannot fully cover for runtime behavior and data-handling.
Active verification is the patented capability that automatically retests identified vulnerabilities to confirm exploitability. Findings flagged as confirmed exploitable get prioritized. Theoretical findings get demoted. The result is a backlog with materially fewer false positives than SAST or DAST alone produce. Sensitive-data tracking is the second patented capability and traces data flow through the running application to identify where PII, payment data, or other sensitive fields are processed unsafely.
Seeker requires QA cycles to produce signal. The platform is the right tool for programs with mature functional or automated testing. Programs without QA discipline get less from Seeker than the marketing implies because the agent has nothing to instrument against. Merito's standard rollout pairs Seeker deployment with a QA-coverage assessment so the customer understands which application surfaces will produce signal and which will not.
Ideal use cases
What it is best at
Patented active verification automatically retests identified vulnerabilities and confirms whether they are exploitable. Confirmed-exploitable findings get prioritized; theoretical findings get demoted. The backlog reflects real risk rather than theoretical detections.
Traces PII, payment data, and other sensitive fields through the running application to identify unsafe handling. Catches data-flow vulnerabilities that pure SAST and DAST cannot reason about.
Agents instrument running applications and analyze interactions during manual or automated tests. Programs with mature QA discipline get security findings as a byproduct of testing they already run.
Seeker findings emerge alongside functional test results inside CI/CD pipelines. Programs avoid the operational lift of running a separate security-only scan cycle.
Core capabilities
How Seeker actually detects vulnerabilities in running applications.
Agent-based instrumentation
Agents deploy alongside the application and instrument runtime behavior. Coverage works during manual tests, automated tests, or any combination.
Real-time vulnerability detection
Findings emerge during testing rather than during a separate scan cycle. Programs see security signal alongside functional test results.
Broad language and framework runtime coverage
Java, .NET, Node.js, Python, Ruby, and other major application stacks get runtime instrumentation depth.
The patented capability that grounds prioritization in confirmed exploitability.
Automated retest on detection
Findings get automatically retested to confirm whether they are exploitable. Confirmed-exploitable findings get prioritized.
Theoretical-finding demotion
Findings that cannot be confirmed exploitable get demoted in the backlog. Reduces false-positive review burden.
Real-time prioritization signal
Security teams see prioritized findings as testing happens rather than waiting for post-scan triage.
Where Seeker catches data-flow vulnerabilities pure SAST and DAST cannot.
PII and payment data flow tracking
Traces sensitive fields through the running application from input to storage or external transmission.
Unsafe-handling detection
Identifies where sensitive data is logged, transmitted insecurely, or stored without encryption.
API call and data-egress analysis
Inspects API calls and external data transmission for sensitive-data exfiltration patterns.
How Seeker findings reach the broader AppSec program.
CI/CD pipeline integration
Seeker results emerge alongside functional test results inside Jenkins, GitHub Actions, GitLab CI, Azure Pipelines, and Bitbucket Pipelines.
Polaris correlation
Findings flow into the Polaris unified findings surface alongside SAST, SCA, and DAST output.
Software Risk Manager correlation
IAST findings flow into Software Risk Manager (ASPM) for cross-tool correlation across the broader AppSec stack.
Where it fits in the stack
Deployment and implementation
Licensing and packaging
Seeker Interactive (SaaS)
SaaS-hosted IAST platform with agent deployment in customer test environments.
Best for: Programs preferring SaaS operations and continuous Black Duck-managed updates.
Seeker Interactive (on-prem)
Customer-hosted IAST platform with full data-residency control.
Best for: Programs with regulatory or operational requirements that mandate on-prem deployment.
Merito services
Merito sells licenses and the delivery work around them. Pick the service that matches where you are in the lifecycle.
Agent deployment, sensitive-data baseline configuration, active verification tuning, and CI/CD integration.
Explore service02AppSec program scoping for IAST adoption alongside Contrast Security, Hdiv, and other IAST options.
Explore service03Seeker integration into CI/CD pipelines and QA test orchestration. Findings routing into developer ticketing.
Explore service04Named engineer, priority SLAs, and release-window coverage for Seeker in production.
Explore service05Long-term run support including ongoing agent maintenance, sensitive-data baseline tuning, active verification calibration, and triage operating-model evolution.
Explore service06Role-based training for AppSec engineers, QA leaders, and developers using Seeker findings.
Explore serviceSeeker licensing
IAST works when QA cycles are mature and the data baseline is configured. Buy Seeker through Merito and get the agent deployment, sensitive-data baseline, active verification tuning, and CI/CD integration together.
Merito point of view
Seeker is the right tool for programs with mature functional or automated testing. The agent has something to instrument, the active verification has data to retest against, and the findings emerge as a byproduct of testing the customer is already running. Programs without QA discipline get less from Seeker than the marketing implies and should mature SAST and SCA first.
Active verification is genuinely a differentiator. Pure SAST scanners produce theoretical vulnerabilities. Pure DAST scanners produce application-level findings without code-path context. Seeker's runtime instrumentation plus active verification produces a backlog with materially fewer false positives. Sensitive-data tracking adds the data-flow visibility most programs underestimate.
Seeker is not a SAST replacement. The product covers a different layer of the AppSec stack and works best layered with SAST and SCA programs that already produce signal. Merito recommends Seeker for programs with strong QA discipline and PCI, HIPAA, or GDPR data-flow requirements. Programs without QA maturity should sequence SAST and SCA first.
What buyers usually underestimate
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Frequently Asked Questions
Consultation request
Share your QA program, current AppSec stack, and sensitive-data flow concerns. A Merito Seeker specialist follows up within one business day.
Active verification
Patented active verification automatically retests findings. Confirmed-exploitable get prioritized. Theoretical get demoted.
Sensitive-data tracking
Traces PII, payment data, and other sensitive fields through the running application. Catches data-handling vulnerabilities pure SAST and DAST miss.
Next step
A Seeker engagement with Merito starts with the QA-coverage assessment, then agent deployment, then sensitive-data baseline. Programs with strong QA discipline see signal inside their existing test cycles.