Attacks and malicious behavior
Detect supported hostile or suspicious activity through observable patterns and context rather than assuming identity alone establishes intent.
API Threat Detection
API Threat Detection that connects evidence to runtime action.
Proxyble continuously evaluates API-consumer behavior to detect supported attacks, suspicious activity, anomalies, and reconnaissance during production traffic. Threat evidence informs configurable runtime enforcement within the broader Runtime API Governance platform.
- Continuous Threat Detection
- Behavioral Evidence
- Client & Endpoint Context
- Programmable Enforcement
Continuous Threat Detection
Suspicious API activity evaluated across behavior, clients, endpoints, and time
-
Unusual probing appears
A client begins requesting uncommon endpoints in sequence
Activity observedIndividual requests remain contextual -
Reconnaissance pattern develops
Endpoint discovery behavior persists across the client history
Evidence accumulatedSequence and identity considered -
Threat context is evaluated
Behavior, endpoint, risk, and policy inputs inform a decision
Finding qualifiedAnomaly is not treated as proof alone -
Runtime policy responds
Configured enforcement applies to the supported threat pattern
Action enforcedEvidence remains available for review
- Detection
- Continuous
- Evidence
- Behavioral
- Decision
- Contextual
- Response
- Runtime policy
What API threat detection covers
API threat detection continuously identifies supported hostile activity, suspicious patterns, anomalies, reconnaissance, and policy violations targeting APIs. Threat-led detection is the focus; broader abuse-control outcomes belong under API Abuse Protection.
Reconnaissance and enumeration
Identify documented probing, endpoint discovery, and enumeration behavior without inventing universal indicators.
Anomalies and policy violations
Treat deviations and prohibited behavior as evidence requiring client, endpoint, identity, risk, and policy context.
Why request-level and static controls can miss threats
Identity, signatures, request inspection, and static thresholds remain valuable. Evolving, distributed, contextual, and low-and-slow threats may also require evidence accumulated across consumers, endpoints, requests, and time.
Attackers
Automation
Compromised Identity
Services
Integrations
Authorized Clients
Point-in-time controls ×Request inspection×Identity alone×Static thresholds Necessary evidence. Incomplete threat history.
Threats during API operation
Detect supported suspicious and hostile patterns in or adjacent to the request path while established controls remain in place.
Requests gain context over time
Sequences, persistence, distribution, and changing behavior may reveal supported threats that isolated inspection cannot.
Authenticated traffic can become suspicious
Identity remains an input, while compromised credentials, partners, services, or integrations may still exhibit threatening behavior.
Low-rate activity can accumulate evidence
Supported persistent patterns may become visible across time even when individual activity remains below a fixed threshold.
Continuous behavioral threat detection
Proxyble evaluates supported API-consumer behavior, sequences, identity, endpoint use, anomalies, risk, and suspicious patterns during runtime traffic. Exact models, scores, baselines, and classifications should be confirmed for your deployment.
How API threat detection works
API attack monitoring and threat monitoring supply runtime evidence; they are not the complete outcome. Proxyble connects continuous evaluation to contextual policy decisions and configured enforcement.
1Observe supported traffic
Collect available consumer, identity, endpoint, request-sequence, anomaly, and policy signals during production use.
2Build behavioral evidence
Relate documented activity across requests and time without assuming an unsupported threat score or baseline model.
3Evaluate threat context
Assess supported suspicious patterns with available client, endpoint, identity, risk, and policy context.
4Inform immediate policy
Send the finding and its evidence to configurable runtime policy rather than stopping at retrospective monitoring.
API threat detection with enforcement
Behavior-Informed Adaptive Policy Enforcement connects detection to immediate, programmable runtime action. Here, response means enforcement against supported API traffic—not full incident response, investigation, remediation, case management, or SOAR.
Threat evidence
Supported behavior and contextual signals provide the basis for a policy decision.
Contextual decision
Configured policy may use behavior, identity, client, endpoint, risk, and other documented runtime inputs.
Programmable action
Operators define supported enforcement conditions and actions rather than relying on opaque automatic blocking.
Proportional control
Policies may use proportional responses where documented, without publishing an unsupported fixed action ladder.
Threat patterns within the defined scope
These patterns remain concise and qualified. Abuse control, credential stuffing, bot activity, scraping, and workflow misuse each need controls tailored to their distinct signals and impact.
API reconnaissance detection
Identify supported probing or endpoint-discovery patterns where documented signals are available.
API enumeration detection
Evaluate supported enumeration behavior as reconnaissance across endpoints, identifiers, and time.
Low-and-slow attack detection
Use behavioral history to identify supported persistent low-rate threats while routing broad abuse-control outcomes separately.
Credential attack detection
Cover broad supported credential-related behavior; credential stuffing needs detection and protection tailored to automated login patterns.
Explore API Bot Protection
Detect supported automated attack behavior; general bot identification and governance need controls matched to automated-client behavior.
Scraping and workflow threats
Address harvesting and application-logic-specific patterns with controls tailored to those behaviors.
Business logic attacks
Address workflow and application-logic misuse with policies tailored to the affected API flow.
Threat detection alongside existing security controls
Proxyble provides API Threat Detection within a Runtime API Governance platform. It complements WAF or WAAP controls, gateways, IAM, SIEM, observability, static limits, and broader API-security tooling rather than broadly replacing them.
API Consumers
Anonymous, authenticated, human, service, and automated
Existing Controls
Identity, routing, request inspection, limits, and telemetry
Proxyble
Behavioral threat evidence and contextual runtime policy
Production APIs
Endpoints and application resources during live operation
Keep request inspection, identity, gateway, telemetry, and investigation responsibilities in place.
Add consumer behavior, endpoint context, and threat evidence to supported runtime decisions.
Apply configured traffic-path enforcement while SIEM and security operations retain broader response roles.
- WAF and WAAP retain request inspection and threat intelligence
- Gateways retain routing, authentication, and API management
- IAM and OAuth retain identity and access responsibilities
- SIEM and observability retain telemetry and investigation
- Static limits remain useful volume controls
- DDoS and CDN infrastructure retain volumetric protection
- Runtime API Governance
- Behavioral API Security
- WAF / WAAP
- API Gateways
- IAM / OAuth
- SIEM / Observability
Evaluate API threat detection through evidence
An API threat detection platform or solution should substantiate its supported threat classes, signals, behavioral context, policy connection, enforcement conditions, and measurement methodology.
Supported threat classes
Verify documented attacks, anomalies, reconnaissance, enumeration, credential activity, automation, and low-rate scenarios.
Detection mechanics
Confirm supported signals, windows, client semantics, endpoint context, and how evidence is accumulated.
Policy and enforcement
Review documented policy inputs, operator controls, actions, conditions, timing, and evidence records.
Qualified measurements
Assess coverage, accuracy, false positives, latency, throughput, and overhead only with defined methodology and conditions.
API Threat Detection questions
API threat detection continuously identifies supported attacks, suspicious activity, anomalies, reconnaissance, and policy-violating behavior targeting APIs during operation. Proxyble uses behavioral evidence to inform contextual runtime policy.
API Threat Detection is detection-led and focuses on hostile or suspicious activity. API Abuse Protection owns the broader outcome of controlling malicious and authorized-client abuse.
Combine request and identity controls with continuous evaluation of supported consumer behavior, sequences, endpoint use, anomalies, and patterns over time, then connect findings to configurable runtime enforcement.
No. Anomalous behavior is evidence that should be evaluated with available client, endpoint, identity, risk, policy, and behavioral context.
Supported persistent low-rate patterns may be identified through behavioral evidence accumulated across time. Exact observation conditions and scenarios should be confirmed for your deployment.
Supported probing, endpoint-discovery, and enumeration behavior may be detected where documented signals, targets, identifiers, and observation windows are available.
Broad supported credential-related threat behavior may be covered. Credential stuffing needs detection and protection tailored to automated login patterns.
Supported automated attack behavior may be detected. General bot identification and automated-client governance require policies matched to those behaviors.
No. Monitoring supplies evidence, while Proxyble connects supported findings to contextual decisions and configured runtime enforcement.
No. Response means immediate programmable enforcement against supported runtime API traffic. Investigation, remediation, case management, and SOAR remain outside the stated scope.
No universal automatic-blocking claim is made. Policies are contextual, configurable, and operator-defined, with proportional controls where documented.
Behavioral, identity, client, endpoint, risk, and policy context can inform programmable and proportional enforcement. False positives cannot be ruled out or assigned a numerical rate without evidence.
Detection and decisions occur during runtime traffic. Quantitative latency claims require defined hardware, workload, percentile, configuration, and measurement boundaries.
No. Proxyble complements request inspection, routing, identity, telemetry, and investigation, and competes selectively where behavioral detection plus active runtime enforcement is required.
No universal coverage claim is approved. Detection must be scoped to supported attack classes, available signals, configured policies, and documented conditions.
Behavioral context, supported signals, policy inputs, and decision evidence should only be described where documented, including their fields, retention, and interpretation.
Evaluate API Threat Detection
against your threat scenarios.
Review supported threat classes, behavioral evidence, policy controls, runtime enforcement, architecture, and qualified security measurements with Proxyble.