Investigating Aws Incidents logo

Investigating Aws Incidents

Community
trilwu
investigating-aws-incidents

Investigate security incidents in Amazon Web Services -- reconstruct attacker activity from CloudTrail, VPC Flow Logs, and GuardDuty, anchor the investigation on the compromised principal (access key or role), trace privilege escalation and persistence through IAM API calls, detect data exfiltration and crypto-mining, and contain without destroying evidence or tipping off the attacker. Use when responding to a suspected AWS compromise, exposed access keys, anomalous CloudTrail activity, a GuardDuty finding, unexpected IAM changes, crypto-mining EC2 instances, or S3 data exfiltration.

Overview

Publishertrilwu
Repositorysecskills
Skill nameinvestigating-aws-incidents
Stars
144
Forks
15
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by trilwu on GitHub. Read the source before you install it.

Installation

Install the Investigating Aws Incidents AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/trilwu/secskills.git /tmp/secskills
mkdir -p .claude/skills
cp -r /tmp/secskills/secskills-defense/skills/investigating-aws-incidents .claude/skills/investigating-aws-incidents
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Investigating Aws Incidents in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Investigating Aws Incidents on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Investigating Aws Incidents is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Investigating AWS Incidents

In AWS an incident is reconstructed from logs the attacker usually could not delete -- CloudTrail, VPC Flow Logs, and the control plane's own record of every API call. The investigation is therefore a log-correlation exercise anchored on the compromised principal: the access key or assumed role, and the sequence of API calls it made. Find the principal, pull every event it generated, and the rest of the intrusion falls out of the timeline.

When to Use

  • Exposed or leaked AWS access keys -- committed to a repo, in a pastebin, or flagged by AWS abuse
  • Anomalous CloudTrail activity -- API calls from unfamiliar regions, IPs, or user agents
  • A GuardDuty finding -- credential exfiltration, tor traffic, crypto-mining, or anomalous IAM behavior
  • Unexpected IAM changes -- new users, keys, roles, login profiles, or policy attachments nobody authorized
  • Crypto-mining EC2 -- a spike in on-demand instances, GPU families, or an unexpected billing alert
  • S3 data exfiltration -- GetObject spikes, buckets made public, or shared snapshots

When NOT to Use

  • The incident is in Microsoft 365 / Entra ID, not AWS -- use investigating-m365-entra
  • The incident is in Azure resources/subscriptions -- use investigating-azure-incidents
  • The incident is in Google Cloud -- use investigating-gcp-incidents
  • The general IR process and host-level response -- use responding-to-incidents
  • You are the attacker, not the responder -- use exploiting-cloud-platforms
  • The pivot is specifically into Kubernetes on EKS -- use attacking-eks-gke-aks
  • Proactive hunting with no confirmed incident -- use hunting-threats

First-Hour Triage

Three actions, in order: identify the principal, pull its recent activity, preserve before you contain.

Scope the compromised principal. Whether the report is a leaked key, a GuardDuty finding, or a billing spike, resolve it to a single principal ARN -- an IAM user, a role, or the root account. That ARN is the anchor for everything that follows.

bash
# What is this key/session, and does it still work?
aws sts get-caller-identity                       # if you hold the suspect creds
# Resolve an access key ID to its owner
aws iam get-access-key-last-used --access-key-id AKIA...
# Enumerate the principal's current footprint
aws iam list-access-keys --user-name <user>
aws iam list-attached-user-policies --user-name <user>
aws iam list-user-policies --user-name <user>

Pull recent activity from the principal. Event history (below) is the fastest first look; the S3 log bucket is the source of truth.

bash
aws cloudtrail lookup-events \
  --lookup-attributes AttributeKey=Username,AttributeValue=<user> \
  --start-time 2026-07-01T00:00:00Z --max-results 200

# By access key -- catches role sessions that lookup-by-username misses
aws cloudtrail lookup-events \
  --lookup-attributes AttributeKey=AccessKeyId,AttributeValue=AKIA...

Isolate without tipping off -- snapshot then contain. An attacker who sees their key deactivated mid-operation will burn persistence you have not found yet. For anything but active, ongoing damage: preserve evidence first (snapshot volumes, export logs), map persistence, then contain everything at once. If there is live damage -- active mining, active exfil -- stop the damage and accept the trade.

CloudTrail Deep-Dive

Event history vs. the S3 log bucket. The console Event history is searchable but covers only 90 days of management events and drops data events. The CloudTrail S3 log bucket (or CloudTrail Lake) is the authoritative record and the only place with S3/Lambda data events -- query it, not the console, once you are past the first look. Confirm what is actually logged:

bash
aws cloudtrail describe-trails
aws cloudtrail get-trail-status --name <trail>          # IsLogging: true?
aws cloudtrail get-event-selectors --trail-name <trail> # data events on?

userIdentity types tell you what you are looking at:

typeMeaningInvestigative note
IAMUserLong-lived user credentialsaccessKeyId is the pivot. Human or service account?
AssumedRoleTemporary STS credsRead sessionContext.sessionIssuer for the source role.
AWSServiceAn AWS service actingUsually benign, but check for spoofed-looking service calls.
RootRoot accountAlmost never legitimate for API calls. Treat as critical.
FederatedUser / WebIdentityUserGetFederationToken broker / OIDC web identityTrace to the broker's IAM user, or the IdP session.

For AssumedRole, sessionContext.sessionIssuer.arn names the role and sessionContext.attributes.mfaAuthenticated tells you whether MFA was used.

Anomaly fields to grep:

  • sourceIPAddress -- external IPs on role credentials that should only run inside the VPC (the IMDS theft signature, below). Correlate against VPC Flow Logs.
  • userAgent -- aws-cli/2.x, Boto3, python-requests, or anything with kali on a principal that normally shows console or SDK-from-Lambda agents.
  • awsRegion -- calls in regions you do not operate in (attackers spin up mining in ap-* / sa-* to dodge attention). Enumeration touches many regions fast.
  • errorCode -- a storm of AccessDenied / UnauthorizedOperation is enumeration: the attacker is mapping what the stolen principal can do.
sql
-- Athena over the CloudTrail S3 bucket: AccessDenied enumeration storm
SELECT eventname, count(*) AS n
FROM cloudtrail_logs
WHERE useridentity.accesskeyid = 'AKIA...'
  AND errorcode = 'AccessDenied'
  AND eventtime > '2026-07-01T00:00:00Z'
GROUP BY eventname ORDER BY n DESC;

Canonical Attacker API Patterns

Grep the timeline for this sequence. It is the shape of nearly every stolen-key intrusion:

  • GetCallerIdentity -- often the very first call. The attacker is confirming what the key is and who owns the account.
  • Enumeration -- List* / Get* / Describe* across IAM, S3, EC2, RDS, Secrets Manager, often with an AccessDenied storm.
  • Privilege escalation -- CreateUser, CreateAccessKey, AttachUserPolicy (watch for AdministratorAccess), PutUserPolicy (inline policy so it does not show in attached-policy lists), CreateLoginProfile (a console password on an API-only account), UpdateLoginProfile.
  • iam:PassRole abuse -- passing a high-privilege role to a new EC2 instance, Lambda, or Glue job to inherit its permissions. Look for PassRole paired with RunInstances / CreateFunction.
  • Trust-policy tampering -- UpdateAssumeRolePolicy or CreateRole with a trust policy naming an external account (a cross-account backdoor).
  • STS chaining -- AssumeRole into a more privileged role, then another, building a chain that launders the original stolen key.
bash
# Pull the IAM mutating calls for the window
aws cloudtrail lookup-events \
  --lookup-attributes AttributeKey=EventName,AttributeValue=CreateAccessKey
# Repeat for: CreateUser, AttachUserPolicy, PutUserPolicy, CreateLoginProfile,
#             UpdateAssumeRolePolicy, CreateRole, AssumeRole
# (iam:PassRole is a permission, not an event -- find it in requestParameters of
#  RunInstances / CreateFunction, not via lookup-by-EventName)

Persistence Hunting

Enumerate every mechanism explicitly during eradication -- rotating the one leaked key does nothing about a second one the attacker created.

  • New IAM users / keys / roles created inside the incident window.
  • A second access key on an existing user -- CreateAccessKey on the victim or another account; a user may have up to two keys.
  • Console login profiles on service accounts -- CreateLoginProfile on a principal that never used the console is high-signal.
  • Modified role trust policies -- UpdateAssumeRolePolicy adding an external principal or sts:AssumeRole from another account.
  • Lambda backdoors -- a new or updated function that mints credentials or re-creates users, often on an EventBridge schedule.
  • EventBridge / CloudWatch Events rules invoking attacker Lambda on a cron.
  • iam:CreateServiceLinkedRole and other quietly-privileged roles.
bash
# Users and keys created recently
aws iam list-users --query 'Users[?CreateDate>=`2026-07-01`].[UserName,CreateDate]'
for u in $(aws iam list-users --query 'Users[].UserName' --output text); do
  aws iam list-access-keys --user-name "$u" \
    --query 'AccessKeyMetadata[].[UserName,AccessKeyId,CreateDate]' --output text
done

# Roles whose trust policy names an external account
aws iam list-roles --query 'Roles[].[RoleName,AssumeRolePolicyDocument]'

# Recently modified Lambda and the EventBridge rules that fire them
aws lambda list-functions --query 'Functions[].[FunctionName,LastModified]'
aws events list-rules --query 'Rules[].[Name,ScheduleExpression,State]'

IMDS / SSRF Credential Theft Signatures

The classic AWS escalation: an SSRF or foothold on an EC2 instance reads the Instance Metadata Service (http://169.254.169.254/latest/meta-data/iam/...), lifts the instance role's temporary credentials, and uses them elsewhere.

The signature is unmistakable in CloudTrail: the instance role's session credentials appear from a sourceIPAddress that is not the instance. The role is minted for the instance, so any call from an external or unrelated IP means the credentials left the box.

sql
-- Role session creds used from outside the VPC
SELECT eventtime, eventname, sourceipaddress, useragent
FROM cloudtrail_logs
WHERE useridentity.arn LIKE '%assumed-role/<instance-role>%'
  AND sourceipaddress NOT LIKE '10.%'
  AND sourceipaddress NOT LIKE '172.%'
ORDER BY eventtime;

IMDSv1 (a simple GET, no session token) makes this trivial and is itself a finding -- confirm whether the instance enforces IMDSv2 (HttpTokens: required) via aws ec2 describe-instances. Correlate the theft window with VPC Flow Logs for the outbound SSRF and the reuse source.

GuardDuty Finding Triage

GuardDuty is a starting pistol, not the investigation. Each finding type maps to a hypothesis you confirm in CloudTrail:

Finding typeImplication
UnauthorizedAccess:IAMUser/InstanceCredentialExfiltration.*Instance role creds used off the instance -- the IMDS theft above.
UnauthorizedAccess:IAMUser/MaliciousIPCallerA principal called from a known-bad IP.
UnauthorizedAccess:IAMUser/TorIPCallerAPI calls via Tor -- almost never a legitimate admin.
CryptoCurrency:EC2/BitcoinTool.B!DNSAn instance talking to a mining pool -- confirmed crypto-mining.
Recon:IAMUser/*Enumeration -- the AccessDenied storm.
Persistence:IAMUser/*, PrivilegeEscalation:IAMUser/*IAM mutation matching the escalation patterns above.
Policy:S3/BucketAnonymousAccessGrantedA bucket was made public -- possible exfil staging.
bash
aws guardduty list-findings --detector-id <id> \
  --finding-criteria '{"Criterion":{"severity":{"Gte":4}}}'
aws guardduty get-findings --detector-id <id> --finding-ids <id>

Findings older than the CloudTrail window still carry the principal and IPs -- pivot on those even when the raw events have aged out of Event history.

Data-Theft Detection

  • S3 GetObject spikes -- a jump in GetObject volume/bytes on sensitive buckets, visible only if S3 data events are logged. Check request counts by principal.
  • Buckets made public -- PutBucketPolicy / PutBucketAcl granting AllUsers or AuthenticatedUsers, or PutPublicAccessBlock disabling the block.
  • Snapshot sharing -- ModifySnapshotAttribute or ModifyImageAttribute adding an external account or all to the volume/AMI (steal data by sharing the snapshot out).
  • RDS exfil -- ModifyDBSnapshotAttribute sharing a DB snapshot, or StartExportTask dumping a snapshot to an attacker-controlled S3 bucket.
sql
SELECT eventname, useridentity.arn, sourceipaddress,
       json_extract_scalar(requestparameters, '$.attributeType') AS attr
FROM cloudtrail_logs
WHERE eventname IN ('ModifySnapshotAttribute','ModifyImageAttribute',
                    'ModifyDBSnapshotAttribute','PutBucketPolicy','PutBucketAcl')
  AND eventtime > '2026-07-01T00:00:00Z';

Anti-Forensics the Attacker Attempts

A capable attacker tries to blind you. Watch for and, crucially, work around:

  • StopLogging / DeleteTrail -- turning off CloudTrail.
  • PutEventSelectors -- narrowing what the trail records (dropping data events or a whole region) without deleting the trail.
  • DeleteFlowLogs -- removing VPC Flow Logs to hide the network side.
  • DeleteDetector / UpdateDetector (disable) / suspend -- killing GuardDuty.

The defeat for all of these is a member-account-independent Organizations-level trail that logs to a central, locked S3 bucket (MFA delete, Object Lock, separate log-archive account) the compromised principal cannot reach. The very act of StopLogging is itself logged there before it takes effect. If you have an org trail, the attacker's cleanup calls are evidence, not gaps. If you do not, note the blind window as a scoping limitation.

bash
# Was logging tampered with? These calls are the finding.
aws cloudtrail lookup-events \
  --lookup-attributes AttributeKey=EventName,AttributeValue=StopLogging
# Repeat: DeleteTrail, PutEventSelectors, DeleteFlowLogs, DeleteDetector

Evidence Preservation

  • EBS snapshots of every involved instance's volumes, before you touch the instance. Tag with the case ID and apply a resource policy / legal hold so they cannot be deleted.

    bash
    aws ec2 create-snapshot --volume-id vol-xxx \
      --description "IR-2026-042 preserve" \
      --tag-specifications 'ResourceType=snapshot,Tags=[{Key=case,Value=IR-2026-042},{Key=legal-hold,Value=true}]'
  • Memory capture on a live instance before termination -- for a resident implant or in-memory creds, this is the only source. Acquire and then analyze per analyzing-memory-images.

  • Export the relevant CloudTrail window to a preserved location, and copy VPC Flow Logs and any GuardDuty findings before retention expires.

  • Tagging and legal hold on all evidence artifacts, and involve legal before collection if the incident may become a regulatory or litigation matter.

Containment and Eradication

Do it all at once, after scoping. Partial containment alerts the attacker.

  • Deactivate, do not delete, keys -- deletion destroys the artifact; a deactivated key still shows in the timeline.

    bash
    aws iam update-access-key --user-name <user> \
      --access-key-id AKIA... --status Inactive
  • Revoke active sessions -- deactivating a key does not kill in-flight temporary sessions minted from it. Attach an inline deny policy that invalidates any session/token issued before now (the AWSRevokeOlderSessions pattern):

    bash
    aws iam put-user-policy --user-name <user> \
      --policy-name AWSRevokeOlderSessions \
      --policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Deny",
        "Action":"*","Resource":"*","Condition":{"DateLessThan":
        {"aws:TokenIssueTime":"2026-07-20T00:00:00Z"}}}]}'

    For a role, put an equivalent deny in the role's inline policy or a boundary.

  • Rotate every credential the principal could reach: other keys, secrets in Secrets Manager / SSM the principal read, and any hardcoded creds on compromised instances.

  • Quarantine security group -- move a mining or exfil instance to an SG with no egress rather than terminating it, so memory and disk survive for analysis.

  • Remove attacker persistence -- delete the created users/keys/roles, revert tampered trust policies, remove backdoor Lambda and EventBridge rules -- only after they are documented.

Rationalizations to Reject

  • "GuardDuty didn't alert, so nothing happened." GuardDuty covers a subset of behaviors and depends on being enabled in the right regions. Absence of a finding is not evidence of absence -- the CloudTrail timeline is authoritative.
  • "We rotated the leaked key, so we're done." The leaked key was step one. A second key, a new user, a modified trust policy, or a backdoor Lambda survives rotation. Enumerate every persistence mechanism before you close.
  • "The activity came from an AWS IP range, so it's legitimate." Attackers run their tooling on EC2 too. Correlate the principal, user agent, and behavior -- not just the IP owner.
  • "CloudTrail shows no CreateUser, so there's no persistence." Inline policies (PutUserPolicy), a second access key on an existing user, and modified role trust policies all grant persistence without ever creating a user.
  • "It's just crypto-mining, low priority." Mining means a principal with RunInstances was compromised -- the same access could exfiltrate data or escalate. Mining is the visible symptom, not the scope.
  • "The instance role is low-privilege, so the SSRF doesn't matter." Confirm it. iam:PassRole and AssumeRole chains routinely turn a modest instance role into account-wide access. Trace what the role can reach, don't assume.
  • "Logs only go back 90 days, so the compromise started within 90 days." That is your visibility limit, not the attacker's timeline. Record it as a scoping gap and check the org trail / Lake for longer retention.

References

  • investigating-m365-entra -- the sibling cloud-IR skill for M365 / Entra ID incidents
  • responding-to-incidents -- the general IR process, evidence handling, and host-level response
  • exploiting-cloud-platforms -- the offensive side; how these AWS TTPs are executed
  • attacking-eks-gke-aks -- when the pivot is specifically into Kubernetes on EKS
  • analyzing-memory-images -- working an instance memory capture with Volatility
  • hunting-threats -- proactive hunting when there is no confirmed incident
  • reporting-security-findings -- structuring the incident narrative and deliverable
  • AWS CLI, Athena, and CloudTrail Lake -- query the authoritative logs
  • cloudtrail-partitioner -- partition the CloudTrail S3 bucket for fast Athena queries
  • Prowler -- retrospective posture and misconfiguration assessment of the account
  • stratus-red-team -- emulate AWS attack TTPs to learn what each leaves in CloudTrail
  • AWS Security Incident Response Guide; GuardDuty finding-type reference

Frequently asked questions

What does the Investigating Aws Incidents AI skill do?

Investigate security incidents in Amazon Web Services -- reconstruct attacker activity from CloudTrail, VPC Flow Logs, and GuardDuty, anchor the investigation on the compromised principal (access key or role), trace privilege escalation and persistence through IAM API calls, detect data exfiltration and crypto-mining, and contain without destroying evidence or tipping off the attacker. Use when responding to a suspected AWS compromise, exposed access keys, anomalous CloudTrail activity, a GuardDuty finding, unexpected IAM changes, crypto-mining EC2 instances, or S3 data exfiltration.

Why use Investigating Aws Incidents on TypingMind?

Because you install it once and use it with any model. Investigating Aws Incidents is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Investigating Aws Incidents in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/trilwu/secskills/tree/main/secskills-defense/skills/investigating-aws-incidents. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Investigating Aws Incidents?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Investigating Aws Incidents?

As many as you like. As long as a model supports skills, you can use Investigating Aws Incidents with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Investigating Aws Incidents AI skill free?

Yes. It is published on GitHub by trilwu under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇