Exécutez n'importe quel Skill dans Manus
en un clic

Exécutez n'importe quel Skill dans Manus en un clic

detect-api-anomaly-salesforce

Étoiles3

Forks0

Mis à jour6 juillet 2026 à 04:25

Detect Salesforce API activity by a user or integration outside an operator-maintained baseline of approved clients, source IPs, or event-volume limits. Reads OCSF 1.8 Application Activity (6002) or native records emitted by `ingest-salesforce-event-mon-ocsf`, groups API events by actor and time window, and emits OCSF Detection Finding (2004) tagged with MITRE ATT&CK T1078.004. Use when the user mentions Salesforce API anomaly, suspicious integration, connected app drift, API usage spike, or unexpected source IP. Do NOT use on raw Event Monitoring data before normalization, non-Salesforce logs, or as remediation.

Installation

Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.

Exécuter dans Manus

Source

msaad00

msaad00/cloud-ai-security-skills

Ouvrir le dépôt GitHub Voir les dépôts du créateur

Téléchargement

Exécuter dans Manus

Métiers associésSOC

Basé sur la classification professionnelle SOC

Analystes en sécurité de l'informationProfessions informatiques et mathématiques·SOC 15-1212

Explorateur de fichiers

5 fichiers

SKILL.md

readonly

name	detect-api-anomaly-salesforce
description	Detect Salesforce API activity by a user or integration outside an operator-maintained baseline of approved clients, source IPs, or event-volume limits. Reads OCSF 1.8 Application Activity (6002) or native records emitted by `ingest-salesforce-event-mon-ocsf`, groups API events by actor and time window, and emits OCSF Detection Finding (2004) tagged with MITRE ATT&CK T1078.004. Use when the user mentions Salesforce API anomaly, suspicious integration, connected app drift, API usage spike, or unexpected source IP. Do NOT use on raw Event Monitoring data before normalization, non-Salesforce logs, or as remediation.
purpose	Detect Salesforce API activity outside an operator baseline.
capability	detect
persistence	none
telemetry	stderr_jsonl
privilege_escalation	none
license	Apache-2.0
approval_model	none
execution_modes	jit, ci, mcp, persistent
side_effects	none
input_formats	ocsf
output_formats	native, ocsf
concurrency_safety	stateless
metadata	{"homepage":"https://github.com/msaad00/cloud-ai-security-skills","source":"https://github.com/msaad00/cloud-ai-security-skills/tree/main/skills/detection/detect-api-anomaly-salesforce","version":"0.1.0","frameworks":["OCSF 1.8","MITRE ATT&CK v14","OWASP Top 10"],"cloud":["salesforce"]}

detect-api-anomaly-salesforce

Use when

You normalized Salesforce Event Monitoring data with ingest-salesforce-event-mon-ocsf
You need to detect API activity from unexpected clients, source IPs, or event volume
You want a stateless detector for suspicious integrations and valid-account abuse

Do NOT use

On raw Event Monitoring CSV or JSON before ingestion
On generic web access logs or non-Salesforce SaaS audit events
As remediation; connected-app disablement and session kill need HITL-gated write skills

Detection logic

One pass over Salesforce Application Activity events:

Require producer ingest-salesforce-event-mon-ocsf.
Require unmapped.salesforce.event_family=api.
Group events by actor and SALESFORCE_API_ANOMALY_WINDOW_MINUTES. Default is 60.
Compare clients, source IPs, and event count with SALESFORCE_API_BASELINE_JSON.
When no actor baseline exists, fire if count reaches SALESFORCE_API_ANOMALY_EVENT_THRESHOLD. Default is 25.

Baseline example:

export SALESFORCE_API_BASELINE_JSON='{"005svc":{"client_names":["ApprovedClient"],"ips":["203.0.113.10"],"max_events":100}}'
export SALESFORCE_API_ALLOWED_CLIENTS="InternalGateway"

Output contract

Default output is OCSF Detection Finding (class 2004) with:

deterministic metadata.uid
finding_info.types[] = ["salesforce-api-anomaly", "OWASP-Top-10-A01"]
MITRE ATT&CK T1078.004
actor, reason, event count, clients, source IPs, operations, and raw event IDs in evidence

Severity is HIGH.

Usage

cat salesforce.ocsf.jsonl | python src/detect.py > salesforce-api-findings.ocsf.jsonl

Roadmap

Part of Salesforce vendor story issue #35.

Plus depuis ce dépôt

même dépôt

cspm-azure-cis-benchmark

msaad00/cloud-ai-security-skills

Assess Azure subscriptions against a curated subset of CIS Azure Foundations Benchmark v2.1. Automates 32 high-impact read-only checks across Identity, Defender for Cloud, Storage, Database, Logging, Networking, Compute, Key Vault, and App Service (~53% of the v2.1 benchmark). Use when the user mentions Azure CIS benchmark, Azure storage security, or unrestricted SSH/RDP detection in NSGs. Do NOT use for AWS or GCP; do NOT use to remediate findings (assessment-only, Reader role only); do NOT claim full CIS Azure coverage — only 32 of 60 controls are implemented, see the Roadmap section in this file for the gap.

2026-07-113

ingest-entra-directory-audit-ocsf

msaad00/cloud-ai-security-skills

Convert verified Microsoft Entra directoryAudit events into OCSF 1.8 API Activity (6003). The first slice maps Microsoft Graph directory audit events for service-principal credential changes, app-role grants, and federated identity credential creation into deterministic OCSF records while preserving Entra natural IDs such as id, correlationId, and activityDateTime for SIEM dedupe and downstream correlation. Use when the user mentions Entra audit log ingestion, Microsoft Graph directoryAudit normalization, or feeding Entra identity telemetry into an OCSF pipeline. Do NOT use for Okta System Log, Azure Activity Logs, or as a detector or policy engine — this skill only normalizes verified Microsoft Graph directoryAudit payloads.

2026-07-113

ingest-k8s-audit-ocsf

msaad00/cloud-ai-security-skills

Convert raw Kubernetes audit logs (`audit.k8s.io/v1`) into normalized API activity records, with OCSF as the default wire format and native output as an option. Maps user, source IP, verb, objectRef, and response status with enough fidelity for K8s privilege-escalation and secret-access detectors. Use when the user mentions Kubernetes audit logs, kube-apiserver audit sinks, K8s detection engineering, or feeding K8s audit into a SIEM. Do NOT use for container runtime logs, kubelet logs, or CloudTrail / GCP audit / Azure Activity. Do NOT use as a detection skill; this only normalizes events.

2026-07-113

ingest-okta-system-log-ocsf

msaad00/cloud-ai-security-skills

Convert verified Okta System Log events into OCSF 1.8 or native Identity & Access Management records. The first slice maps session and SSO events to Authentication (3002), user lifecycle and account-control changes to Account Change (3001), app/group membership updates to User Access Management (3005), and a narrow verified set of Okta Verify MFA challenge and denial events to Authentication (3002). It preserves Okta natural IDs such as uuid, published, transaction.id, and authenticationContext.externalSessionId for SIEM-friendly dedupe and correlation. Use when the user mentions Okta System Log ingestion, Okta audit log normalization, cross-vendor identity telemetry, or feeding Okta identity events into an OCSF pipeline or native canonical-first flow. Do NOT use for raw Azure Entra, Google Workspace, or AWS IAM logs. Do NOT use as a detector or policy engine — this skill only normalizes verified Okta event payloads into OCSF or native output.

2026-07-113

detect-aws-access-key-creation

msaad00/cloud-ai-security-skills

Detect successful AWS IAM `CreateAccessKey` API calls against IAM users from OCSF 1.8 API Activity records emitted by ingest-cloudtrail-ocsf. Emits an OCSF 1.8 Detection Finding (class 2004) tagged with MITRE ATT&CK T1098.001 (Additional Cloud Credentials) when a principal creates an access key for an IAM user. Use when the user mentions "AWS access key created", "IAM user key issuance", "additional cloud credentials in AWS", or "T1098.001 via CloudTrail". Do NOT use as a posture-at-rest access-key inventory check, to infer console-password or login-profile creation, or to claim every AWS identity-pivot path. This first slice only covers successful `CreateAccessKey` operations.

2026-07-103

detect-mcp-tool-drift

msaad00/cloud-ai-security-skills

Detect MCP tool schema drift mid-session — the MCP tool-poisoning / rug-pull attack pattern. Reads OCSF 1.8 Application Activity (class 6002) or the native application-activity projection produced by ingest-mcp-proxy-ocsf, groups them by session, and flags any tool whose fingerprint (sha256 over name + description + inputSchema + annotations) changes between tools/list responses in the same session. Emits OCSF 1.8 Detection Finding (class 2004) with MITRE ATT&CK T1195.001 (Compromise Software Supply Chain) inside finding_info.attacks. Use when the user mentions MCP security, tool drift, tool poisoning, prompt injection via tool schema, or supply chain compromise of an MCP server. Do NOT use on raw MCP proxy logs — feed them through ingest-mcp-proxy-ocsf first. Do NOT use for cross-session drift (same tool, different sessions) — that is a legitimate MCP server update, not an attack; a separate detector will cover it. Do NOT use for divergence against an out-of-band server-registered baseline — that is detect-m

2026-07-103

name	detect-api-anomaly-salesforce
description	Detect Salesforce API activity by a user or integration outside an operator-maintained baseline of approved clients, source IPs, or event-volume limits. Reads OCSF 1.8 Application Activity (6002) or native records emitted by `ingest-salesforce-event-mon-ocsf`, groups API events by actor and time window, and emits OCSF Detection Finding (2004) tagged with MITRE ATT&CK T1078.004. Use when the user mentions Salesforce API anomaly, suspicious integration, connected app drift, API usage spike, or unexpected source IP. Do NOT use on raw Event Monitoring data before normalization, non-Salesforce logs, or as remediation.
purpose	Detect Salesforce API activity outside an operator baseline.
capability	detect
persistence	none
telemetry	stderr_jsonl
privilege_escalation	none
license	Apache-2.0
approval_model	none
execution_modes	jit, ci, mcp, persistent
side_effects	none
input_formats	ocsf
output_formats	native, ocsf
concurrency_safety	stateless
metadata	{"homepage":"https://github.com/msaad00/cloud-ai-security-skills","source":"https://github.com/msaad00/cloud-ai-security-skills/tree/main/skills/detection/detect-api-anomaly-salesforce","version":"0.1.0","frameworks":["OCSF 1.8","MITRE ATT&CK v14","OWASP Top 10"],"cloud":["salesforce"]}

detect-api-anomaly-salesforce

Use when

You normalized Salesforce Event Monitoring data with ingest-salesforce-event-mon-ocsf
You need to detect API activity from unexpected clients, source IPs, or event volume
You want a stateless detector for suspicious integrations and valid-account abuse

Do NOT use

On raw Event Monitoring CSV or JSON before ingestion
On generic web access logs or non-Salesforce SaaS audit events
As remediation; connected-app disablement and session kill need HITL-gated write skills

Detection logic

One pass over Salesforce Application Activity events:

Require producer ingest-salesforce-event-mon-ocsf.
Require unmapped.salesforce.event_family=api.
Group events by actor and SALESFORCE_API_ANOMALY_WINDOW_MINUTES. Default is 60.
Compare clients, source IPs, and event count with SALESFORCE_API_BASELINE_JSON.
When no actor baseline exists, fire if count reaches SALESFORCE_API_ANOMALY_EVENT_THRESHOLD. Default is 25.

Baseline example:

export SALESFORCE_API_BASELINE_JSON='{"005svc":{"client_names":["ApprovedClient"],"ips":["203.0.113.10"],"max_events":100}}'
export SALESFORCE_API_ALLOWED_CLIENTS="InternalGateway"

Output contract

Default output is OCSF Detection Finding (class 2004) with:

deterministic metadata.uid
finding_info.types[] = ["salesforce-api-anomaly", "OWASP-Top-10-A01"]
MITRE ATT&CK T1078.004
actor, reason, event count, clients, source IPs, operations, and raw event IDs in evidence

Severity is HIGH.

Usage

cat salesforce.ocsf.jsonl | python src/detect.py > salesforce-api-findings.ocsf.jsonl

Roadmap

Part of Salesforce vendor story issue #35.