--- name: implementing-security-information-sharing-with-stix-bf3205822486 description: 'Create, validate, and share STIX 2.1 threat intelligence objects using the stix2 Python library. Covers indicators, malware, campaigns, relationships, bundles, and TAXII 2.1 publishing. ' domain: cybersecurity subdomain: threat-intelligence tags: - stix - taxii - threat-sharing - intelligence-exchange version: '1.0' author: Krishna Kumar (xalgord) license: Apache-2.0 d3fend_techniques: - File Metadata Consistency Validation - Application Protocol Command Analysis - Identifier Analysis - Content Format Conversion - Message Analysis nist_csf: - ID.RA-01 - ID.RA-05 - DE.CM-01 - DE.AE-02 --- # Implementing Security Information Sharing with STIX 2.1 Build and share structured threat intelligence using STIX 2.1 objects with the stix2 Python library and TAXII 2.1 transport protocol. ## When to Use - Building a threat intelligence platform that exchanges IOCs with partner organizations - Automating ingestion and export of indicators from MISP, OpenCTI, or other TIP platforms - Creating machine-readable intelligence reports for ISAC/ISAO sharing communities - Publishing threat data to a TAXII 2.1 server for downstream consumption by SIEMs and SOARs - Converting unstructured threat reports into standardized STIX 2.1 bundles - Enriching detection rules with context by linking indicators to malware, campaigns, and threat actors **Do not use** for sharing simple IP blocklists or CSV-based IOC feeds that do not require relationship context; plain-text feeds with simpler formats like CSV or OpenIOC may be more efficient in those cases. ## Common Misconfigurations & Verification - **Dangling relationship refs:** a `Relationship` whose `source_ref`/`target_ref` points to an object not in the bundle parses fine but breaks consumers. Verify every SRO endpoint resolves to an SDO/SCO `id` present in the bundle. - **Invalid STIX patterns:** patterns like `[file:hashes.'SHA-256' = '...']` require correct property paths and quoting; a malformed `MATCHES` regex or missing bracket fails silently in some loaders. Lint with `stix2-validator`. - **Missing required properties:** custom or hand-built objects dropping `type`/`id`/`created`/`modified` fail spec validation - always construct via the `stix2` library rather than raw dicts. - **TAXII media-type errors:** publishing without `Content-Type: application/taxii+json;version=2.1` (or the matching accept header) yields 406/415 or silent rejection. Confirm `success_count` equals the number of objects sent. - **TLP marking omitted:** objects without `object_marking_refs` default to unrestricted sharing - attach the correct TLP marking definition before publishing. - **Verification:** re-parse the serialized bundle with `allow_custom=False`, round-trip published objects back from the TAXII collection to confirm no data loss, and run `stix2_validator` on the export. ## Prerequisites - Python 3.8+ with `stix2` library (`pip install stix2`) - `taxii2-client` for consuming TAXII feeds (`pip install taxii2-client`) - A TAXII 2.1 server endpoint for publishing (e.g., OpenTAXII, Medallion, or MISP TAXII service) - Familiarity with STIX 2.1 SDO types: Indicator, Malware, Threat Actor, Campaign, Attack Pattern, Identity - Familiarity with STIX 2.1 SRO types: Relationship, Sighting - Optional: OpenCTI or MISP instance for end-to-end integration testing ## Workflow ### Step 1: Install Dependencies ```bash pip install stix2 taxii2-client requests ``` ### Step 2: Create STIX 2.1 Domain Objects (SDOs) Create core intelligence objects that describe threats, actors, and campaigns: ```python from stix2 import ( Indicator, Malware, ThreatActor, Campaign, AttackPattern, Identity, Relationship, Bundle, ExternalReference ) from datetime import datetime # Create a producer identity producer = Identity( name="ACME Threat Intel Team", identity_class="organization", sectors=["technology"], contact_information="threatintel@acme.example.com" ) # Create a malware object emotet_malware = Malware( name="Emotet", description="Banking trojan turned modular botnet loader. " "Distributed via malspam with macro-enabled Office documents.", malware_types=["trojan", "bot"], is_family=True, created_by_ref=producer.id ) # Create an attack pattern referencing MITRE ATT&CK spearphishing_pattern = AttackPattern( name="Spearphishing Attachment", description="Adversaries send spearphishing emails with a malicious attachment.", external_references=[ ExternalReference( source_name="mitre-attack", external_id="T1566.001", url="https://attack.mitre.org/techniques/T1566/001/" ) ], created_by_ref=producer.id ) # Create a threat actor threat_actor = ThreatActor( name="Mummy Spider", description="Cybercriminal group operating the Emotet botnet infrastructure.", threat_actor_types=["crime-syndicate"], aliases=["TA542", "Gold Crestwood"], primary_motivation="personal-gain", created_by_ref=producer.id ) # Create a campaign campaign = Campaign( name="Emotet Q1 2026 Resurgence", description="Renewed Emotet distribution campaign using thread-hijacked " "reply-chain emails with OneNote lure attachments.", first_seen="2026-01-15T00:00:00Z", created_by_ref=producer.id ) print(f"Created malware SDO: {emotet_malware.id}") print(f"Created threat actor SDO: {threat_actor.id}") print(f"Created campaign SDO: {campaign.id}") ``` ### Step 3: Create STIX Indicators with Patterns Define detection patterns using the STIX Patterning Language: ```python # File hash indicator hash_indicator = Indicator( name="Emotet dropper hash", description="SHA-256 hash of Emotet first-stage dropper observed in Jan 2026 campaign.", indicator_types=["malicious-activity"], pattern_type="stix", pattern="[file:hashes.'SHA-256' = 'a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4e5f6a1b2']", valid_from="2026-01-15T00:00:00Z", created_by_ref=producer.id ) # Network indicator for C2 domain c2_indicator = Indicator( name="Emotet C2 domain", description="Command and control domain observed in Emotet tier-1 botnet infrastructure.", indicator_types=["malicious-activity"], pattern_type="stix", pattern="[domain-name:value = 'malicious-c2.example.com']", valid_from="2026-01-20T00:00:00Z", created_by_ref=producer.id ) # Compound pattern: process spawning with suspicious command line process_indicator = Indicator( name="Emotet PowerShell download cradle", description="PowerShell execution pattern used by Emotet to download next-stage payload.", indicator_types=["malicious-activity"], pattern_type="stix", pattern=( "[process:command_line MATCHES 'powershell.*-enc.*' " "AND process:parent_ref.name = 'winword.exe']" ), valid_from="2026-01-15T00:00:00Z", created_by_ref=producer.id ) # Email subject indicator email_indicator = Indicator( name="Emotet phishing subject line pattern", description="Subject line pattern seen in thread-hijacked Emotet phishing emails.", indicator_types=["malicious-activity"], pattern_type="stix", pattern="[email-message:subject MATCHES '^RE:.*Invoice.*[0-9]{6}']", valid_from="2026-01-15T00:00:00Z", created_by_ref=producer.id ) print(f"Created {4} indicator objects") ``` ### Step 4: Build Relationships Between Objects Link SDOs together using Relationship objects to express how threats are connected: ```python # Malware uses attack pattern rel_malware_attack = Relationship( relationship_type="uses", source_ref=emotet_malware.id, target_ref=spearphishing_pattern.id, description="Emotet is distributed via spearphishing attachments.", created_by_ref=producer.id ) # Threat actor uses malware rel_actor_malware = Relationship( relationship_type="uses", source_ref=threat_actor.id, target_ref=emotet_malware.id, description="Mummy Spider operates the Emotet malware infrastructure.", created_by_ref=producer.id ) # Indicator indicates malware rel_indicator_malware = Relationship( relationship_type="indicates", source_ref=hash_indicator.id, target_ref=emotet_malware.id, description="File hash indicator for Emotet dropper binary.", created_by_ref=producer.id ) # Campaign uses malware rel_campaign_malware = Relationship( relationship_type="uses", source_ref=campaign.id, target_ref=emotet_malware.id, created_by_ref=producer.id ) # Threat actor attributed to campaign rel_actor_campaign = Relationship( relationship_type="attributed-to", source_ref=campaign.id, target_ref=threat_actor.id, created_by_ref=producer.id ) print(f"Created {5} relationship objects linking threat intelligence") ``` ### Step 5: Assemble and Serialize a STIX Bundle Package all objects into a bundle for sharing: ```python import json bundle = Bundle( objects=[ producer, emotet_malware, spearphishing_pattern, threat_actor, campaign, hash_indicator, c2_indicator, process_indicator, email_indicator, rel_malware_attack, rel_actor_malware, rel_indicator_malware, rel_campaign_malware, rel_actor_campaign, ] ) # Serialize to JSON bundle_json = bundle.serialize(pretty=True) # Write bundle to file for sharing with open("emotet_campaign_bundle.json", "w") as f: f.write(bundle_json) print(f"Bundle {bundle.id} contains {len(bundle.objects)} objects") print(f"Written to emotet_campaign_bundle.json") # Validate the bundle by re-parsing from stix2 import parse parsed = parse(bundle_json, allow_custom=False) print(f"Bundle validation passed: {len(parsed.objects)} objects parsed successfully") ``` ### Step 6: Consume Intelligence from a TAXII 2.1 Server Retrieve published threat intelligence from a TAXII feed: ```python from taxii2client.v21 import Server, Collection, as_pages import json # Connect to a TAXII 2.1 server taxii_server = Server( "https://taxii.example.com/taxii2/", user="readonly", password="readonly_password" ) # Discover API roots and collections api_root = taxii_server.api_roots[0] print(f"API Root: {api_root.title}") for collection in api_root.collections: print(f" Collection: {collection.title} (ID: {collection.id})") # Fetch indicators from a specific collection target_collection = Collection( f"https://taxii.example.com/taxii2/collections/{api_root.collections[0].id}/", user="readonly", password="readonly_password" ) # Retrieve objects with filtering response = target_collection.get_objects( added_after="2026-01-01T00:00:00Z", type=["indicator", "malware"] ) stix_data = json.loads(response.text) print(f"Retrieved {len(stix_data.get('objects', []))} objects from TAXII server") # Process each retrieved object for obj in stix_data.get("objects", []): if obj["type"] == "indicator": print(f" Indicator: {obj['name']} | Pattern: {obj['pattern'][:60]}...") elif obj["type"] == "malware": print(f" Malware: {obj['name']} | Family: {obj.get('is_family', False)}") ``` ### Step 7: Publish Intelligence to a TAXII 2.1 Server Push your STIX bundle to a writable TAXII collection: ```python import requests import json TAXII_URL = "https://taxii.example.com/taxii2/collections/COLLECTION_ID/objects/" TAXII_USER = "publisher" TAXII_PASS = "publisher_password" headers = { "Content-Type": "application/taxii+json;version=2.1", "Accept": "application/taxii+json;version=2.1" } # Read the bundle we created earlier with open("emotet_campaign_bundle.json", "r") as f: bundle_data = f.read() response = requests.post( TAXII_URL, headers=headers, auth=(TAXII_USER, TAXII_PASS), data=bundle_data, timeout=30 ) if response.status_code in (200, 201, 202): status = response.json() print(f"Published successfully. Status ID: {status.get('id')}") print(f" Total count: {status.get('total_count')}") print(f" Success count: {status.get('success_count')}") print(f" Failure count: {status.get('failure_count')}") else: print(f"Publishing failed: {response.status_code} - {response.text}") ``` ### Step 8: Validate and Lint STIX Objects Ensure objects comply with the STIX 2.1 specification: ```python from stix2 import parse, exceptions import json def validate_stix_bundle(bundle_path): """Validate all objects in a STIX bundle against the 2.1 spec.""" with open(bundle_path, "r") as f: raw = json.load(f) errors = [] valid_count = 0 for obj in raw.get("objects", []): try: parsed = parse(json.dumps(obj), allow_custom=False) valid_count += 1 except (exceptions.InvalidValueError, exceptions.MissingPropertiesError) as e: errors.append({ "object_id": obj.get("id", "unknown"), "object_type": obj.get("type", "unknown"), "error": str(e) }) print(f"Validation results: {valid_count} valid, {len(errors)} errors") for err in errors: print(f" ERROR in {err['object_type']} ({err['object_id']}): {err['error']}") return len(errors) == 0 validate_stix_bundle("emotet_campaign_bundle.json") ``` ## Verification - Confirm all STIX objects serialize to valid JSON and include required properties (`type`, `id`, `created`, `modified`) - Verify relationship `source_ref` and `target_ref` point to existing object IDs within the bundle - Validate indicator patterns parse correctly using the STIX patterning grammar - Test TAXII publishing returns a success status with `success_count` matching the number of objects sent - Re-retrieve published objects from the TAXII server and confirm they round-trip without data loss - Check that consuming systems (SIEM, SOAR, TIP) can ingest the bundle and create corresponding detection rules or enrichment data - Run `stix2-validator` CLI tool against exported bundles: `stix2_validator emotet_campaign_bundle.json` --- Source attribution: xalgord Original project: https://github.com/xalgord/xalgorix/blob/cec44d71b1d998208e1e2091982d0ee2f928041f/internal/tools/skills/data/threat-intelligence/implementing-security-information-sharing-with-stix2/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: xalgord Original project: https://github.com/xalgord/xalgorix/blob/cec44d71b1d998208e1e2091982d0ee2f928041f/internal/tools/skills/data/threat-intelligence/implementing-security-information-sharing-with-stix2/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Development & Engineering Roles: Data Scientist, ML / AI Engineer, Security Engineer Specialties: API Tools: Stix2, Taxii2 Client Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: a3422f852aeed9f8d26a6ae829e9169bb8e9951a7a39ef0e45d4fb977ae7317e