Attempt report

DLP flagged customer records pasted into an unsanctioned public AI chatbot

CybersecurityShadow AI Sensitive-Data ExposureDifficulty · Easy

Attempt 1 of 1 · cmqa60biz00000k3djr2wl1cm

← All attempts ↻ Retry this scenario New scenario

Progress vs previous attempt

This is your first attempt for this scenario. Retry the scenario to generate a side-by-side comparison against your previous response.

Progression · Keep practicing

Stay on Easy · Cybersecurity

3 signals are blocking advancement to Medium. Keep practicing at Easy until those areas stabilize. (Track: Cybersecurity)

Track · Cybersecurity

Easy

Sample · 5 recent attempts2 positive3 blocking

Signals helping

Dangerous action frequency. None in recent attempts
Rubric category coverage. 67% average (need ≥ 55%)

Signals blocking advancement

Recent average score. 65 / 100 (need ≥ 75)
Recent pass rate. 1 of 5 passed (need ≥ 66%)
Recent retry improvement trend. Score is regressing (-11.5 pts on later attempts)

Submission · what was sent and how you responded

Shadow AI Sensitive-Data ExposureDifficulty · easyHigh asset

DLP alert — customer data + code pasted into a public AI chatbot (shadow AI)

From: Maria Lopez <maria.lopez@acme-corp.com>
To: soc@acme-corp.com
Date: 2026-05-04 14:18 UTC

Hi SOC, Our DLP / web proxy flagged a possible data exposure and I want a second opinion before I talk to the user. A Support team member (jordan.kim) used a PERSONAL account on a public AI chatbot from their work laptop and pasted in what looks like a chunk of a customer export plus a snippet of an internal script. This is NOT one of our approved tools — it is "shadow AI". The paste was about 30 minutes ago. Jordan says they were "just trying to summarize a ticket backlog faster". I have the DLP match details and the proxy log. I have not contacted Jordan yet and I have not changed anything. What is the right order of steps, and how do I work out exactly what was exposed and who needs to know? — Maria (SOC, Tier 1)

Evidence

DLP match summary + web-proxy log excerpt (JORDAN-WKS)

# DLP match (endpoint agent)
time:      2026-05-04 13:47 UTC
user:      jordan.kim@acme-corp.com   host: JORDAN-WKS
action:    clipboard paste into browser -> chat.example-ai[.]com (category: Generative AI, UNSANCTIONED)
rule hit:  "Customer PII (name+email+phone)" x42 rows, "Source code (internal)" x1 block
sample:    [REDACTED by DLP] 42 rows matching <name,email,phone,acct_id>; ~60 lines of an internal helper script

# Web proxy (src=10.12.51.30 JORDAN-WKS)
13:46:55  CONNECT chat.example-ai[.]com:443   ALLOW (no GenAI category block configured)
13:47:10  POST    chat.example-ai[.]com/api/conversation   (request body not inspected — TLS)
13:51:02  GET     chat.example-ai[.]com/   200

# Tool / account context
- chat.example-ai[.]com = public consumer AI chat, PERSONAL login (not SSO, not in the app catalog)
- no enterprise data-retention setting, no DPA / contract with this vendor
- Support role scope: read access to the customer ticket system + a customer-export report

Affected asset

Name: Customer records (42) + internal script snippet via jordan.kim
Type: Regulated customer PII export + internal source snippet pasted into an unsanctioned public AI chatbot
Owner: Customer Support · Jordan Kim (data owner: Support Ops / Privacy)
Level: High

Your submitted response

65 words

Containment: isolate the affected host from the network and disable the compromised account. Investigation: preserve system and authentication logs, then review sign-in events to scope the intrusion. Recovery: rotate affected credentials, patch the exploited vector, and restore from a known-good backup after validation. Prioritization: contain first, then investigate, then recover. Evidence: capture volatile memory and a disk image before remediation to preserve chain of custody.

Final score

13/ 100

65 words submitted

Verdict · Fail

The response is missing several critical incident response steps. Review the rubric and try again. Score: 13/100. Strongest area: Clarity & structure (53%). Weakest area: Attack understanding (0%) — expand this next time.

Category breakdown

Where points came from

coverage × weight = points

Attack understanding0/3 · 0.0 / 15
Asset impact0/3 · 0.0 / 10
Prioritization0/2 · 0.0 / 10
1/5 · 4.0 / 20
Investigation0/4 · 0.0 / 15
Recovery0/3 · 0.0 / 10
Evidence preservation1/3 · 3.3 / 10
Clarity & structure1/2 · 5.3 / 10

Strengths

No category reached 70% coverage.

Missing / weak

Attack understanding
Asset impact
Prioritization
Investigation
Recovery
Evidence preservation

Dangerous actions detected

None detected in your response.

Learning · Coaching

Learn from this attempt

Post-submission coaching for this scenario. Score and verdict are unchanged — these notes are for your next attempt.

Why points were deducted

Attack understanding0% coverage
Name this as shadow-AI / unsanctioned-tool data exposure (sensitive data sent to a third-party GenAI service), not a malware or account-compromise incident.
Investigation0% coverage
Use the DLP match + proxy log to pin the exact records and fields, check for repeat / other-tool use, and trace the source export.
Asset impact0% coverage
Identify regulated customer PII (42 rows, specific fields) AND internal source — and that the vendor has no DPA / data-retention control, so the data is now outside your boundary.

Model answer outline

From: Incident Response Lead (SOC on-call)To: IT Leadership · Affected Asset Owner · On-call SOCSubject: [SEV-3][INC-CYB-E5061] DLP flagged customer records pasted into an unsanctioned public AI chatbot — status update

Incident · INC-CYB-E5061 · SEV-3 / P3Status · Investigating — containment in progressCybersecurity · Shadow AI Sensitive-Data Exposure · EasyCustomer records (42) + internal script snippet via jordan.kim · High criticalityDetected ~ 2026-05-04 14:18 UTC

Situation & summary

A Support user (jordan.kim) pasted ~42 rows of customer PII (name/email/phone/acct_id) plus a ~60-line internal script into a public consumer AI chatbot (chat.example-ai[.]com) from their work laptop, using a personal login on an unsanctioned tool with no DPA and no enterprise data-retention. DLP and the web proxy caught it ~30 minutes ago. This is a shadow-AI data-exposure incident, not malware — the job is to scope what left, contain further exposure, preserve the evidence, and bring in the data owner / Privacy.

Severity & priority

Rated SEV-3 / P3. Treat as a P2 confirmed data-exposure: regulated customer PII left to a third party with no contract, but it is bounded and already detected.

Prioritization & impact

Treat as a P2 confirmed data-exposure: regulated customer PII left to a third party with no contract, but it is bounded and already detected.
Scope what was exposed BEFORE deciding on notification — the record count and fields drive whether this is a reportable privacy event.
Loop in the data owner (Support Ops) and Privacy/Legal early; keep it factual and non-punitive so the user keeps cooperating.

Containment (actions taken / in progress)

Add a GenAI / unsanctioned-AI category block (and block chat.example-ai[.]com) at the proxy so the same paste cannot be repeated fleet-wide.
Tell Jordan to stop using the tool and not to paste the data again; do not have anyone re-enter the data to 'test' it.
Request deletion of the conversation from the vendor and opt out of any training use, and flag the 42 affected account ids to the data owner to watch.

Investigation (in progress)

From the DLP match and proxy log, establish exactly what was pasted (42 PII rows + which fields, and the internal script), not just that 'something' was.
Check whether Jordan (or others) did this before or with other GenAI sites — one paste or a pattern changes the response.
Identify the source of the export (which report / ticket query) so the data owner can confirm the records and classification.

Recovery & next steps

Stand up or point users to a sanctioned AI option so the productivity need that drove the shadow use has a safe path.
Tighten DLP / proxy policy for GenAI categories and add the lesson to acceptable-use / AI-usage policy.
Run a short, blameless awareness refresher for Support on what may and may not be pasted into external tools.

Evidence preservation

Preserve the DLP match record and the web-proxy log entries (export, do not delete) with the case id.
Capture a screenshot / record of the tool, account type, and timestamps before any policy change.
Record the affected record count and fields for the Privacy/Legal assessment.

Stakeholder communication

Brief the data owner (Support Ops) and Privacy/Legal with the concrete scope (42 records, fields, source).
Coach Jordan factually on what happened and what to do instead — reporting and cooperation should not feel punished.
Hold any external/customer notification until Privacy/Legal complete the reportability assessment.

Do NOT

Do not delete the DLP alert or clear the proxy logs — they are the evidence of what was exposed.
Do not re-paste the data into the chatbot to 'reproduce' it — that repeats the exposure.
Do not forward the exposed customer records around over email/chat while investigating.
Do not jump to discipline before scoping; punitive first moves discourage future reporting.

Dangerous actions to avoid

Do not delete the DLP alert or clear the proxy logs — they are the evidence of what was exposed.
Do not re-paste the data into the chatbot to 'reproduce' it — that repeats the exposure.
Do not forward the exposed customer records around over email/chat while investigating.
Do not jump to discipline before scoping; punitive first moves discourage future reporting.

How to improve next time

Shadow AI is a data-governance incident: the core question is always 'what data left, to whom, under what contract' — answer that before anything else.
Blocking the GenAI category at the proxy contains the whole fleet, not just one user; pair it with a sanctioned alternative so people do not route around it again.
Never reproduce a data-exposure by re-entering the data — you would be exposing it a second time.
Scope drives notification: the record count, fields, and customer identities determine whether Privacy/Legal must report it.
Keep shadow-AI response blameless and factual; punishing the first reporter teaches everyone else to hide the next one.

AI · Supplemental review

Request an AI review of this attempt

This AI review is supplemental coaching. It does not change your official score or verdict. The review is only kept for this page session and is not saved permanently.

Review languageEnglishKorean

AI Tutor · Explains your result

AI Tutor

This tutor explains your result. It does not change your score. Pick a question to see how the deterministic grading reached your verdict and where to focus next.

Generated deterministically from your graded result — no AI model was called.

Why did I get this score?

Your verdict was Fail at 13/100. That total is the sum of deterministic rubric points across 8 categories — each scores how much of its expected, ordered steps your answer covered, not an opinion about your writing. Your strongest coverage was Clarity & structure (53%). Points were held back mostly in Attack understanding (0%), Investigation (0%), Asset impact (0%).

Rubric focusattackUnderstandinginvestigationassetImpact

Next study step

Re-read the attack understanding expectations for this scenario and list the concrete steps you missed.