Incident Management

This is the standard the Quality Gate's Reliability lens holds work to for the moment something goes wrong in production. It covers the whole arc of an incident: how anyone raises one, how we respond and meet our legal duties, and how AI helps us investigate without widening the blast radius. It builds on the Infrastructure Planning Policy (which gives us backups, RPO/RTO targets, and reversible deploys), the Security Policy (what we protect and the risks we assume), and the pull-request discipline of the Development Guide. Deviations are allowed, but — as everywhere in the handbook — they must be deliberate and justified in the project's design notes.

An incident is where OSBR's values are tested hardest. Be Nice: we keep stakeholders informed, on time, in plain language, and we never hand a tired on-call human a change they did not ask for. Be Kind: the person who reports an incident — or caused one — is doing us a favour by surfacing it, so the report is thanked and the post-mortem is blameless; we fix systems, not people. Be Strong: we face the incident directly, contain it, tell the client the truth even when it hurts, and know when to call for help. Humans and AI agents work an incident here as collaborators — and that partnership carries a specific hazard, live production, that this policy names head-on (§3).

How to read this policy

• Requirement levels follow RFC 2119, as in the Coding Style Guide. MUST / MUST NOT are absolute. SHOULD / SHOULD NOT state a strong default overridable only with a documented reason. MAY marks a free choice.
• Named practice. Where a rule adopts an industry practice — NIST SP 800-61, SANS PICERL, the incident-command patterns of Google SRE and PagerDuty — the practice is named inline and cited under References. We adopt the criteria of these practices and right-size them for an SME; we do not adopt the headcount or infrastructure behind their reference setups.
• This is guidance, not legal advice. The reporting deadlines and thresholds in §2-3 are OSBR's default reading of the law. For any serious personal-data incident, confirm the current obligation with the client's legal counsel. When in doubt, notify.

• How to read this policy

• 1. Reporting an Incident

  • 1-1. The reporter does not decide whether it is an incident
  • 1-2. Where to report — speed beats formality
  • 1-3. What to report — the three points
  • 1-4. Report regardless of scale or certainty
  • 1-5. No blame for reporting in good faith

• 2. Responding to an Incident

  • 2-1. One owner — the Security Officer as Incident Commander
  • 2-2. Determine type and severity
  • 2-3. Mandatory-reporting obligations
  • 2-4. The five response flows
  • 2-5. Close-out — every incident ends the same way

• 3. AI-Assisted Production Investigation

  • 3-1. Same outputs a human reaches — no private backchannel
  • 3-2. Read-only is the first inviolable boundary
  • 3-3. PII masked before context is the second inviolable boundary
  • 3-4. Mutating actions live on a separate, human-approved path
  • 3-5. Human-in-the-loop — AI diagnoses, a human decides
  • 3-6. Attribution and audit

• References

1. Reporting an Incident

The goal of reporting is to make it fast, safe, and normal for any developer or collaborator to raise a suspected incident, so the Security Officer can act while the situation is still small. The behaviour we want is simple: report early, report often. A rumour of a problem, reported in two minutes, beats a confirmed breach found three days later. This section exists to remove every reason someone might hesitate — uncertainty, embarrassment, fear of blame, or worry about "wasting" the officer's time.

1-1. The reporter does not decide whether it is an incident

This is the single most important rule of reporting:

• The reporter MUST NOT self-triage before reporting. Deciding whether something is "really" an incident is the Security Officer's call, not the reporter's. The reporter's only job is to surface what they noticed.
• Asking individuals to judge severity before speaking up is how real incidents get silently sat on. When in doubt, report — the cost of a false alarm is minutes; the cost of a missed incident is measured in trust and data.

1-2. Where to report — speed beats formality

• Reporters MUST raise suspected incidents in the dedicated #incident-response channel, addressed to the Security Officer.
• Reporters MUST NOT wait to gather a "complete" picture, open a formal ticket first, or route the report through a team lead before speaking up.
• If the dedicated channel is unavailable, reporters SHOULD contact the Security Officer directly (or info@osbrjp.com if the officer is unreachable) and note it in the channel once reachable.
• Reporters MUST NOT attempt to quietly fix a suspected incident alone. A delayed report turns a small incident into a large one.

1-3. What to report — the three points

Every report MUST include these three points. Keep it short; a few sentences each is enough. You are not expected to know the full answer to any of them — "I don't know yet" is a valid and useful answer.

1. Summary — What did you see? A plain description of the symptom (e.g. "prod API is returning other users' data on /orders", "I think I pushed an AWS key to a public repo").
2. Status & certainty — Is it ongoing or over? How sure are you? Say so honestly — "still happening", "not sure if it's real", "90% sure". Low certainty is not a reason to stay silent.
3. Scope of impact — Who or what looks affected, as far as you can tell? Which system, which data, which customers — even a rough guess ("looks like staging only, but I can't confirm prod is safe").

1-4. Report regardless of scale or certainty

• Reporters MUST report even when unsure whether the event qualifies as an incident, and regardless of how small it looks.
• Reporters SHOULD report near-misses too — the thing that almost went wrong. Near-misses are free lessons.
• A report made in good faith that turns out to be nothing is a success, not a mistake. We would rather investigate ten false alarms than miss one real event.

1-5. No blame for reporting in good faith

OSBR operates a blameless / just culture (Dekker), grounded in psychological safety (Edmondson): people only surface problems early when they are confident that doing so will not be held against them. Punishing reporters destroys exactly the early-warning signal we depend on. This is Be Kind made concrete.

• There is no personal penalty for reporting a suspected incident in good faith — including one you caused yourself.
• The Security Officer and team leads MUST respond to reports with thanks and focus on the system and the fix, never on punishing the reporter.
• Every response review and post-incident write-up MUST stay blameless (§2-5): they ask what in the system let this happen and how do we make it harder next time, never who to blame.

2. Responding to an Incident

We do not invent our own incident model. We follow the practices the field has already settled on — NIST SP 800-61, SANS PICERL (Prepare, Identify, Contain, Eradicate, Recover, Lessons-learned), and the incident-command patterns published by Google SRE and PagerDuty — right-sized for a small team. The goal is to detect an incident quickly, contain the damage, meet every mandatory reporting obligation on time, restore verified service, and make sure the same thing cannot happen the same way twice.

2-1. One owner — the Security Officer as Incident Commander

Every incident has exactly one owner: the on-duty Security Officer, who acts as Incident Commander (IC) in the sense used by Google SRE and PagerDuty. The IC is the single decision-maker; they need not do every task, but own that every task happens.

The Security Officer MUST:

• Declare the incident and take command; hand over explicitly if they step away — no incident is ever ownerless.
• Acknowledge every report promptly so the reporter knows it landed, and make the incident-vs-not determination.
• Determine the incident type and severity (§2-2).
• Assess mandatory-reporting obligations and start those clocks (§2-3).
• Select and drive the applicable response flows (§2-4).
• Own the closing artifacts: blameless post-mortem, recurrence-prevention plan with a verification date, and stakeholder report (§2-5).

The reporter SHOULD stay reachable to answer follow-up questions but is not responsible for running the response unless asked.

Roles scale down, they do not disappear. On a large incident the IC delegates two roles from the same playbooks: an Operations/Tech lead who actually changes the system, and a Communications lead who handles client and internal updates. On a small incident one person may wear all three hats — but the roles still exist, so nothing is dropped.

2-2. Determine type and severity

Before acting, the Security Officer classifies the incident. Classification decides severity, which decides how fast we move and who we wake up.

Type — classify against the risk categories in the Security Policy, Appendix 2 (accidents / human error, external attacks, insider threats), and note whether personal data is in scope, because that triggers the legal duties in §2-3. Typical types: personal-data breach; unauthorised access / account compromise; malware / ransomware; availability incident (ties into the SLO / RTO / RPO targets in the Infrastructure Planning Policy); accidental disclosure or data loss.

Severity — the Security Officer MUST assign a severity at declaration and MUST revise it as facts change. Severity is about impact and reach, not blame, and is set by the officer, never by the reporter.

When unsure between two severities, the officer MUST pick the higher one and de-escalate later. Under the PDPA, APPI, and GDPR the reporting clock can start on a suspected breach, not only a confirmed one (§2-3). Downgrading is cheap; a missed legal deadline is not. Do not under-classify to avoid paperwork.

2-3. Mandatory-reporting obligations

As part of analysis, the Security Officer MUST determine whether a legal notification duty applies and start the clock the moment a breach is reasonably suspected — not when it is fully understood. If a duty applies, the Disclose flow (§2-4) becomes mandatory, not optional.

Malaysia — PDPA (Personal Data Protection Act 2010, Act 709). OSBR's home law. Under the Personal Data Protection (Amendment) Act 2024 (Act A1727), a data controller must notify the Personal Data Protection Commissioner of a personal-data breach as soon as practicable, and notify affected data subjects where the breach is likely to cause significant harm. The regulator is the Personal Data Protection Commissioner / Personal Data Protection Department (JPDP).

Japan — APPI (revised Act on the Protection of Personal Information). A business handling personal information must report a reportable breach to the Personal Information Protection Commission (PPC, 個人情報保護委員会) and notify affected individuals. A breach is reportable when it involves any of: sensitive personal information (要配慮個人情報); a risk of property damage (e.g. leaked payment data); a breach committed for an improper purpose (cyberattack / unauthorised access); or more than 1,000 data subjects. Reporting is two-stage — a preliminary report (速報) promptly, within about 3–5 days of becoming aware, and a final report (確報) within 30 days of awareness (extended to 60 days where the breach was for an improper purpose). If some required items are not yet known by the deadline, file with what is known and complete it as the facts are established.

EU / EEA — GDPR (where applicable). GDPR applies where a project processes the personal data of individuals in the EU/EEA (confirm scope with the client; mind data residency per the Infrastructure Planning Policy). Article 33 — notify the competent supervisory authority without undue delay and, where feasible, within 72 hours of becoming aware, unless the breach is unlikely to result in a risk to individuals; a missed 72-hour mark must be explained. Article 34 — where the breach is likely to result in a high risk to individuals' rights and freedoms, communicate it to the affected data subjects without undue delay.

More than one may apply. A single incident can trigger the PDPA, APPI, and GDPR at once. Track each clock separately — they have different recipients and different deadlines — inside the incident record (§2-4).

2-4. The five response flows

Once type, severity, and reporting duties are set, the Security Officer executes among these five flows. They are not strictly sequential: Record runs throughout, Disclose runs on the legal clock, and Request external assistance can start at any point. The lifecycle maps OSBR's flows onto SANS PICERL and the NIST SP 800-61 phases; a real incident loops back as new facts arrive.

Record · Identify. Open the incident record the moment the incident is declared and keep it current — it is the backbone of every later flow and of any regulator submission. The Security Officer MUST capture: a single, timestamped, append-only timeline of what was observed, decided, and done, by whom; type, severity, and scope (which systems, whose data, how many records); any reporting clocks started (§2-3), with their deadlines; and evidence preserved before it is destroyed — logs, metrics, and communication history are protected assets (Security Policy, Appendix 1). Preserve first; do not tamper while containing. The record SHOULD live in the project's agreed incident location, access-limited to those who need it, with personal data masked per the Security Policy.

Prevent (Contain) · Contain. Stop the bleeding before cleaning up — containment comes before eradication. The Security Officer MUST contain proportionally to severity: revoke or rotate compromised credentials and keys (immediately revoke any committed credential, per the Security Policy); isolate affected hosts, disable compromised accounts, or block malicious traffic at the WAF / edge; and where appropriate throttle or take a service offline rather than let a breach continue — a short outage can beat an ongoing data leak. Containment actions MUST be written to the record as they happen.

Remediate · Eradicate + Recover. Once contained, remove the root cause and restore verified service. The Security Officer MUST: eradicate — remove the attacker's foothold, malware, or the defect and close the vulnerability that allowed the incident, fixing the root cause, not the symptom; recover — restore service from a known-good state and, where data was lost, restore from tested backups against the datastore's RPO / RTO (per the Infrastructure Planning Policy); and verify — confirm the system is clean and healthy through monitoring before declaring recovery, watching for recurrence. Root-cause fixes that cannot ship during the incident become items in the recurrence-prevention plan (§2-5), each with an owner and a verification date.

Disclose · cross-phase, on the legal clock. Tell the people who need to know — honestly, promptly, in plain language. This flow is mandatory whenever §2-3 applies, and good practice even when it does not. The Security Officer (or Communications lead) MUST: file the regulator notifications on their deadlines (PDPA notification to the Personal Data Protection Commissioner as soon as practicable; APPI 速報 / 確報 to the PPC; GDPR Art. 33 to the supervisory authority); notify affected individuals where required (PDPA where significant harm is likely; APPI; GDPR Art. 34 high-risk); keep the client informed from the start — never let a client learn of their own incident from a regulator or the news; and give internal stakeholders honest, timely status updates (Be Nice). Disclosure SHOULD state what happened, what data was involved, what we have done, and what affected parties should do — no spin, no minimising. Every external communication is logged in the record.

Request external assistance · any phase. Knowing when to call for help is Be Strong, not weakness. The Security Officer SHOULD bring in outside help when the incident exceeds the team's capacity or authority: legal counsel for reporting obligations and liability (the default for any SEV1/SEV2 personal-data breach); the cloud provider's security team, or a specialist DFIR (digital-forensics & incident-response) firm for serious intrusions; law enforcement, where the client and counsel agree it is warranted; and the relevant CSIRT / JPCERT-CC-style coordination body where appropriate. External parties are given least-privilege access and recorded in the incident record. Involving them never removes the Security Officer's ownership of the incident.

2-5. Close-out — every incident ends the same way

An incident is not closed when service is restored — it is closed when we have learned from it (the PICERL Lessons-learned phase; NIST Post-Incident Activity). The Security Officer MUST produce all three artifacts below.

• Blameless post-mortem — written in the sense established by Etsy and the Google SRE practice: the analysis assumes everyone acted reasonably with the information they had, and asks how the system let this happen, never who to blame. This is Be Kind made concrete — the reason people report honestly instead of hiding. It MUST cover timeline, impact, root cause(s), what went well, what went badly, and where we got lucky, and MUST NOT name individuals as causes.
• Recurrence-prevention plan (with a verification date) — the concrete actions that stop this class of incident from recurring. Each action MUST have an owner and a verification date — a scheduled point at which someone confirms the fix is in place and effective. A prevention plan with no verification date is a wish, not a plan.
• Stakeholder report — a written report to affected stakeholders (client first, plus internal leadership and, where relevant, regulators and affected individuals): what happened, the impact, what we did, and what we are changing so it does not recur. Plain language, no blame, on time.

3. AI-Assisted Production Investigation

The same structured logs, metrics, and traces that let an on-call engineer find a fault are what let an AI agent investigate one. This section is the access-control and data-handling contract that makes it safe to actually do that in production. The promise is asymmetric on purpose: we want AI to make investigation faster — trace an error to its span, correlate a spike to a deploy, read the error budget, draft the root-cause narrative — without making the blast radius any larger than a human investigator's already is. So AI gets exactly the observer's reach and no more.

Two boundaries are inviolable: every path AI uses to reach production is read-only, and PII is masked before it enters AI context. They are not tunable per project, per incident, or per urgency. A faster investigation is never a reason to widen either one; if a boundary is in the way, the answer is a better read-only view or a better mask, never an exception. Be Nice — AI does the tedious correlation across a hundred thousand log lines so a tired on-call human does not. Be Kind — the people in the telemetry are protected, because their personal data never reaches the model at all. Be Strong — an investigator, human or AI, that can see the whole system reaches root cause faster.

We lean on published standards rather than inventing our own: the principle of least privilege and read-only / just-in-time access (AWS IAM best practices; NIST SP 800-207 Zero Trust), PII de-identification / masking (NIST SP 800-122), data minimisation (GDPR Art. 5(1)(c)), human oversight of AI (NIST AI RMF), and the LLM-specific failure mode of sensitive-information disclosure (OWASP Top 10 for LLM Applications).

3-1. Same outputs a human reaches — no private backchannel

AI investigates through the same observation outputs a human on-call engineer uses — the central log store, the metrics and trace backend — defined by OSBR's observability discipline.

• MUST give AI access to the same telemetry surface humans use, not a bespoke firehose, raw database, or node-level access a human investigator would never touch. Parity of observation, not a wider door.
• MUST NOT grant AI a path to production data that bypasses the observability pipeline's masking and access controls — reading raw production tables, tailing an unmasked log file on a host, or snapshotting memory. If a human investigator should not reach it, neither does AI.
• SHOULD expose telemetry through query tools/APIs (e.g. an MCP server, a read-only observability API) scoped to exactly the observation outputs, so the reach is defined by the tool surface, not by a broad cloud credential.

3-2. Read-only is the first inviolable boundary

Every path AI uses to reach production observation data is read-only, enforced by the permissions of the identity, so that even a confused, prompt-injected, or buggy agent cannot mutate production through its investigation path.

• MUST run all AI production investigation under a dedicated, read-only, least-privilege identity whose permissions include no write, delete, update, restart, scale, deploy, rollback, or configuration-change action on any production resource. Least privilege is the floor; read-only is the ceiling.
• MUST enforce read-only at the permission layer (IAM policy / role / scoped API token), not merely by instructing the model or filtering prompts. A boundary a prompt can talk its way past is not a boundary.
• MUST keep the investigation identity separate from any identity that can mutate production (§3-4). One credential never holds both "read the logs" and "restart the service."
• MUST NOT grant the investigation identity standing high-privilege access "to save a round trip."
• SHOULD scope the identity by time and blast radius where the platform allows — short-lived / just-in-time credentials, read replicas over primaries, environment- and service-scoped tokens.

3-3. PII masked before context is the second inviolable boundary

Personal data is masked or removed before it enters AI context — before the bytes reach the model, not after. This inherits from OSBR's rule that PII must be masked or omitted at the source before it is written to any log, span attribute, or metric label, and from the Security Policy's treatment of telemetry as a Protected Asset. AI adds a second reason the masking must already be done: data placed in a model's context is data minimisation you can no longer take back.

• MUST ensure PII is masked, redacted, tokenised, or pseudonymised at the source so the observation outputs AI reads do not contain raw names, emails, tokens, full card/account numbers, precise location, or request/response bodies carrying personal data. The mask is upstream of AI, not a filter bolted on at query time that a new field can slip past (NIST SP 800-122).
• MUST NOT place unmasked personal data into an AI prompt, tool result, or retained context — including when a human pastes a raw log excerpt into an agent. The masking obligation follows the data, not the pipeline.
• MUST apply data minimisation to what enters context — only the observation data the investigation needs, only for as long as it needs it (GDPR Art. 5(1)(c)).
• SHOULD use stable pseudonymous identifiers (a hashed user id) over raw ones, so AI can correlate "the same user's requests" without ever holding who that user is.
• SHOULD treat any secret, credential, or token found in telemetry as a leaked credential — revoke it and fix the mask that let it through — rather than reasoning about it in context.

3-4. Mutating actions live on a separate, human-approved path

An investigation may conclude that production must change — restart an instance, roll back a deploy, scale a pool, flip a flag, correct a record. That action does not happen on the investigation path; it happens on a separate path gated by explicit human approval, the way high-privilege and break-glass access is gated elsewhere in modern practice (Google Cloud Privileged Access Manager; AWS IAM).

• MUST route every mutating production action through a distinct, human-approved path — a separate identity/role, a change gate, a break-glass procedure — never through the AI investigation identity (§3-2).
• MUST require a human approval step before any change is applied. AI may prepare the action (draft the rollback command, the scaling change, the runbook step); a human approves and applies it. AI approving its own proposed change is prohibited.
• MUST make break-glass / emergency-change use auditable and alerting — who invoked it, when, why, on what. Emergency speed does not buy silence.
• SHOULD prefer pre-decided, automated self-healing for the conditions a machine already handles — a retriable timeout, an unhealthy instance de-routed, a pre-agreed rollback trigger. Those need no live human approval because they were approved when written down. The approval gate here is for the novel change an investigation invents on the spot.

3-5. Human-in-the-loop — AI diagnoses, a human decides

The output of AI-assisted investigation is a proposal, not an executed decision. Keeping a human in the loop for the action is what lets us take the speed of AI investigation without inheriting the risk of an autonomous agent changing production (NIST AI RMF).

• MUST treat AI conclusions as advisory. A root-cause narrative, a suspected bad deploy, a recommended rollback — a human reviews it and owns the decision to act, exactly as they would a colleague's suggestion.
• MUST keep the human able to understand and override the proposal: AI cites the specific traces/logs/metrics it reasoned from (the correlation a shared trace_id makes possible), so the human can check the evidence, not just the conclusion.
• SHOULD let AI do the toil end-to-end within the read-only boundary — fan out across logs, correlate spans, compute the error-budget burn, draft the incident timeline and the post-mortem — so the human spends their judgement on the decision, not the data-gathering.
• SHOULD capture the human's decision (approved / rejected / modified) so the investigation record shows both the AI proposal and the human call.

3-6. Attribution and audit

Both boundaries are only real if their use is visible.

• MUST make every AI query against production observation data attributable to the AI investigation identity and logged, so "what did the agent read" is answerable after the fact — telemetry access is itself a Protected-Asset access (Security Policy).
• MUST log every human-approved mutating action (§3-4) with who approved it, what AI proposed, and why — the change record ties the AI proposal to the human decision to the applied action.
• SHOULD alert on anomalies in the investigation path itself — an investigation identity attempting a write it should not have, an unusual volume of telemetry pulled into context — as a high-signal event.

Anti-patterns this section exists to prevent: handing the investigation agent a broad admin/deploy credential "so it can fix things too"; enforcing read-only only in the prompt while the underlying token can write; masking PII after it reaches the model, or "planning to add masking later"; pasting a raw, unmasked production log dump into an agent because it is faster; letting AI restart, roll back, or scale production on its own conclusion with no human approving; a break-glass change applied with no record of who, what, or why; and AI reaching production data through a backchannel (raw DB, host shell) that bypasses the observability pipeline's masking.

References

Incident-handling frameworks

• NIST SP 800-61 — Computer Security Incident Handling Guide — https://csrc.nist.gov/pubs/sp/800/61/r2/final
• SANS — Incident Handler's Handbook (the PICERL model: Preparation, Identification, Containment, Eradication, Recovery, Lessons-learned) — https://www.sans.org/white-papers/33901/

Incident command & operations

• Google SRE — Managing Incidents (Incident Command System) — https://sre.google/sre-book/managing-incidents/
• PagerDuty Incident Response documentation — https://response.pagerduty.com/

Blameless culture & post-mortems

• Sidney Dekker, Just Culture: Balancing Safety and Accountability — separating honest error from the system that allowed it — https://www.taylorfrancis.com/books/mono/10.1201/9781315251271/just-culture-sidney-dekker
• Amy Edmondson, The Fearless Organization — psychological safety as the precondition for speaking up — https://fearlessorganization.com/
• Etsy — Blameless PostMortems and a Just Culture (John Allspaw) — https://www.etsy.com/codeascraft/blameless-postmortems/
• Google SRE — Postmortem Culture: Learning from Failure — https://sre.google/sre-book/postmortem-culture/

Legal / mandatory reporting

• Malaysia — Personal Data Protection Act 2010 (Act 709), the home law — Personal Data Protection Department (JPDP) — https://www.pdp.gov.my/
• Malaysia — Personal Data Protection (Amendment) Act 2024 (Act A1727), mandatory breach notification to the Personal Data Protection Commissioner (as soon as practicable; affected data subjects where significant harm is likely) — https://www.pdp.gov.my/ppdpv1/en/akta/personal-data-protection-amendment-act-2024/
• Japan — Personal Information Protection Commission (PPC), breach-reporting duty under the revised APPI — https://www.ppc.go.jp/en/
• GDPR Article 33 — Notification of a personal data breach to the supervisory authority (within 72 hours) — https://gdpr-info.eu/art-33-gdpr/
• GDPR Article 34 — Communication of a personal data breach to the data subject — https://gdpr-info.eu/art-34-gdpr/
• GDPR Article 5(1)(c) — Data minimisation — https://gdpr-info.eu/art-5-gdpr/

Least-privilege, read-only & human-approved access

• AWS IAM — Security best practices (least privilege, read-only, just-in-time, short-lived credentials) — https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html
• NIST SP 800-207 — Zero Trust Architecture — https://csrc.nist.gov/pubs/sp/800/207/final
• Google Cloud — Privileged Access Manager (just-in-time elevation, emergency/break-glass access) — https://docs.cloud.google.com/iam/docs/pam-overview

PII masking & AI oversight

• NIST SP 800-122 — Guide to Protecting the Confidentiality of PII (de-identification/masking) — https://csrc.nist.gov/pubs/sp/800/122/final
• NIST AI Risk Management Framework (human oversight; govern/map/measure/manage) — https://www.nist.gov/itl/ai-risk-management-framework
• OWASP Top 10 for LLM Applications (Sensitive Information Disclosure; Excessive Agency) — https://owasp.org/www-project-top-10-for-large-language-model-applications/

Related OSBR standards

• Quality Gate — the Reliability lens this standard serves.
• Security Policy — protected assets, credential hygiene, and the risk categories incidents fall into.
• Infrastructure Planning Policy — backups/DR, RPO/RTO, observability, and reversible deploys that make detection and recovery possible.
• Development Guide — the pull-request discipline that carries root-cause fixes and prevention items.
• Code of Conduct — the behavioural baseline that makes blameless reporting safe.