Terrance DeJesus
4312d8c958
* initial commit * addressing flake errors * added apm to _get_packagted_integrations logic * addressed flake errors * adjusted integration schema and updated rules to be a list * updated several rules and removed a unit test * updated rules with logs-* only index patterns * Update tests/test_all_rules.py Co-authored-by: Mika Ayenson <Mikaayenson@users.noreply.github.com> * addressed flake errors * integration is none is windows, endpoint or apm * adding rules with accepted incoming changes from main * fixed tag and tactic alignment errors from unit testing * adjusted unit testing logic for integration tags; added more exclusion rules * adjusted test_integration logic to be rule resistent and skip if -8.3 * adjusted comments for unit test skip * fixed merge conflicts from main * changing test_integration_tag to remove logic for rule version comparisons * added integration tag to new rule * adjusted rules updated_date value * ignore guided onboarding rule in unit tests * added integration tag to new rule Co-authored-by: Mika Ayenson <Mikaayenson@users.noreply.github.com>
88 lines
3.6 KiB
TOML
88 lines
3.6 KiB
TOML
[metadata]
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creation_date = "2022/07/27"
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integration = ["endpoint"]
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maturity = "production"
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min_stack_comments = "New fields added: required_fields, related_integrations, setup"
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min_stack_version = "8.3.0"
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updated_date = "2022/12/14"
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[rule]
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author = ["Elastic"]
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description = "This rule identifies a high number (10) of process terminations via pkill from the same host within a short time period."
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from = "now-9m"
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index = ["logs-endpoint.events.*"]
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language = "kuery"
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license = "Elastic License v2"
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name = "High Number of Process Terminations"
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note = """## Triage and analysis
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### Investigating High Number of Process Terminations
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Attackers can kill processes for a variety of purposes. For example, they can kill process associated
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with business applications and databases to release the lock on files used by these applications so they may be
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encrypted,or stop security and backup solutions, etc.
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This rule identifies a high number (10) of process terminations via pkill from the same
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host within a short time period.
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#### Possible investigation steps
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Detection alerts from this rule indicate High Number of Process Terminations from the same host
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Here are some possible avenues of investigation:
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- Examine the entry point to the host and user in action via the Analyse View.
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- Identify the session entry leader and session user
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- Examine the contents of session leading to the process termination(s) via the Session View.
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- Examine the command execution pattern in the session, which may lead to suspricous activities
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- Examine the process killed during the malicious execution
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- Identify imment threat to the system from the process killed
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- Take necessary incident response actions to respawn necessary process
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### False positive analysis
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- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
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### Response and remediation
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- Initiate the incident response process based on the outcome of the triage.
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- Isolate the involved host to prevent further destructive behavior, which is commonly associated with this activity.
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- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are
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identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business
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systems, and web services.
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- Reimage the host operating system or restore it to the operational state.
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- If any other destructive action was identified on the host, it is recommended to prioritize the investigation and look
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for ransomware preparation and execution activities.
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- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and
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malware components.
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- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
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- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the
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mean time to respond (MTTR).
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"""
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risk_score = 47
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rule_id = "67f8443a-4ff3-4a70-916d-3cfa3ae9f02b"
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severity = "medium"
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tags = ["Elastic", "Host", "Linux", "Threat Detection", "Impact", "Investigation Guide"]
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type = "threshold"
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query = '''
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event.category:process and event.type:start and process.name:"pkill" and process.args:"-f"
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'''
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[[rule.threat]]
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framework = "MITRE ATT&CK"
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[[rule.threat.technique]]
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id = "T1489"
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name = "Service Stop"
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reference = "https://attack.mitre.org/techniques/T1489/"
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[rule.threat.tactic]
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id = "TA0040"
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name = "Impact"
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reference = "https://attack.mitre.org/tactics/TA0040/"
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[rule.threshold]
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field = ["host.id"]
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value = 10
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