T1696.002 Avoid CAPTCHA — Attack Simulation

Complete technique description

Adversaries may avoid CAPTCHA challenges by mimicking human behavior. Automation tests, such as CAPTCHA, are typically used by defenders to detect and prevent bot and spam traffic from accessing protected webpages. CAPTCHAs are often placed before login screens or form fields. Traditional CAPTCHAs ask the user to decipher a string of characters, type the characters into a box, and submit the form. reCAPTCHA asks the user to identify images, click a checkbox, or evaluate the user’s behavior from mouse movement and device cookies.[CAPTCHAS Cloudflare]

Adversaries may attempt to avoid CAPTCHA challenges by constructing a bot that mimics human behavior through browser automation. The automated browser may mimic a human by Masquerading a Browser Fingerprint and through attributes such as session history, IP reputation, and the use of browser APIs.[CAPTCHA Bypass Olostep] For example, adversaries may use Selenium browsers to simulate a human user. In the Selenium browsers, JavaScript is injected into the website’s Document Object Model (DOM). The injected script may modify browser attributes such as Audio Context and Voice engines, graphic rendering, installed fonts, and browser navigator objects.[Sentinel CAPTCHA Bypass]

Official technique definition · Open in the interactive matrix

Parent and sub-techniques

• T1696 Anti-Automation Evasion — parent

Related pages are navigation context. Their tools, rules and lab results are not automatically inherited.

Detection telemetry and configuration

These contracts are selected through exact technique-to-data-component relationships or explicitly labelled planning overrides. Configure a collector at the relevant observation point; a telemetry name alone is not coverage.

No source-mapped collection contract is available for T1696.002. Read the technique-specific MITRE guidance below to determine what is observable and which party controls that data.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

Before treating a rule as coverage

1. Read the actual condition and logsource; identify attacker-side, victim-side or third-party visibility.
2. Map native sensor fields, parse times and identities, then compile for the selected backend.
3. Replay a behavior-positive case, a normal control, an authorized look-alike and a missing-telemetry case.
4. Record matches and misses with rule version and source events. No match is inconclusive when required telemetry is absent.

Anomaly-based detection

No exact technique-specific Atlas model is present for T1696.002 in the selected source snapshot. The following is a design worksheet, not a newly validated model.

Anomaly engineering worksheet

Start from the exact analytic above. The collection-specific lenses below are analyst recommendations; they do not assert that an arbitrary statistical deviation detects this technique.

Resolve the observation point before defining measurable features. Private attacker preparation can be outside victim visibility.

1. Define an entity/peer group and feature; exclude the evaluation period from baseline training.
2. Use representative normal and maintenance activity. Do not invent a production threshold from a synthetic example.
3. Evaluate held-out behavior-positive and benign cases; measure false positives, misses and telemetry loss separately.
4. Keep abnormality separate from maliciousness. Correlate with the behavior-specific source evidence.

Anomaly Detection Atlas · Baseline, validation and blind spots

Attack tools and documented software

No reviewed lab-tool association is selected for this exact technique. This is a curation gap, not a statement that no tool can implement the behavior.

Simulation design and documented procedures

Atomic evidence: no compatible candidate in this snapshot. Live lab status: not run for these imported procedures.

Use disposable lab hosts and test accounts, explicit target allowlists, a clean snapshot, bounded egress and a restore plan. Review every candidate and dependency before any execution.

No compatible Atomic procedure is present in this pinned evidence set. Technical feasibility has not been ruled out. A custom procedure must define the behavior, target, collection point, success observable and rollback before execution.

Technique-specific experiment contract

1. Choose one procedure implementing T1696.002 Avoid CAPTCHA; identify the observable behavior in the source definition, not just its tactic.
2. Record exact target, tool/version, inputs, privileges, network limits and approval. Never run an imported default target automatically.
3. Enable the collection sources above and verify a benign baseline reaches the detector.
4. Run only the approved isolated scenario; capture native events and an independent behavior observable.
5. Evaluate the exact rule/model, restore the lab, and preserve configuration, event hashes, alerts, controls and misses.

Synthetic logs and offline contract check

No synthetic event is invented when the relevant collection point is unresolved. Download the workbook and define the observable source with the system owner first.

Validation status and remaining work

Source identity

Joined by exact technique/object IDs against hash-pinned sources.

Collection fixture

Not supplied because no collection contract is available.

Native telemetry / backend / real attack

Not validated for these imported procedures. Source fidelity and page tests cannot establish sensor or detector effectiveness.

All-page audit and evidence inventory · This page’s machine-readable workbook

Sources and evidence boundaries

Pinned MITRE STIX source · SHA-256 81113ba98afa2928f3dcff62022539f7ce30c315c32e14422f11ff95ce534352. Definition and procedure context are reproduced from this snapshot, not independently re-investigated incidents.

• mitre-attack
• Sentinel CAPTCHA Bypass
• CAPTCHA Bypass Olostep
• CAPTCHAS Cloudflare