System & Network Access Logs

• Records IP addresses, timestamps, and user sessions associated with account access.
• Helps correlate suspicious login events (e.g., from unexpected locations or times) with possible account takeover activity.

• Captures user authentication events, IP addresses, timestamps, and changes to account settings (e.g., email, phone).
• Allows detection of unusual or repeated contact detail updates following large inbound 'fee' payments, a common indicator in advance fee fraud schemes.

• Captures network traces, IP addresses, authentication events, and multi-hop routing paths.
• Helps investigators observe the use of layered encryption or repeated connections from Tor, VPNs, or proxy servers, pinpointing suspicious anonymity-driven access during financial transactions.

• Captures IP addresses, user authentication events, and device information associated with transaction initiations.
• Helps identify unusual device usage or script-driven accesses that can indicate automated or bot-driven transfers.
• Enables correlation of suspicious transaction patterns with specific login events and potential unauthorized system activities.

• Track user logins, attempted logins, and changes to system configurations (e.g., AML thresholds, security settings).
• Provide timestamps, user credentials, and activity trails to help investigators detect unauthorized overrides or suspicious after-hours access to administrative functions.
• Facilitate the identification of insider collusion by correlating access patterns with altered AML triggers or disabled security protocols.

• Tracks user activities, including overrides and clearance of high-risk transactions.
• Identifies unauthorized modifications to AML controls, indicative of bribed insiders covering illicit transactions.

• Captures IP addresses, authentication events, and device fingerprints correlated with blockchain bridging transactions.
• Identifies irregular login patterns and rapid device or IP changes that align with cross-chain hops, suggesting potential illicit access or layered laundering attempts.

• Contains IP addresses, device fingerprints, login timestamps, and other network metadata.
• Identifies cases where multiple purportedly separate player accounts share common access points, indicating potential collusion.
• Assists in uncovering suspicious account overlaps, rapid logins from the same device, and other anomalies consistent with chip dumping schemes.

• Captures user actions within internal systems, including timestamps, login details, and administrative overrides.
• Identifies repeated or unjustified suppression of AML alerts, manual overrides of monitoring rules, and other complicit staff activities.
• Enables auditors and investigators to trace potential internal collusion that allows illicit transactions to remain undetected.

Tracks user authentication events, IP addresses, device fingerprints, and account activities across multiple platforms. This reveals potential connections or repeat logins indicative of coordinated cross-game transfers or clandestine 'gifting' strategies.

• Captures login events, IP addresses, and network usage patterns.
• Identifies VPN or proxy usage that may hide the true location of mining equipment or cloud-based services.
• Helps detect anomalous remote access and potential obfuscation methods used by illicit miners.

Provides details of user sessions, device resource usage (e.g., CPU/GPU consumption), IP addresses, and network connections. This information helps detect unauthorized cryptomining software or unusual outbound traffic to cryptomining pools, enabling timely identification and investigation of cryptojacking activities.

• Captures user access points, including IP addresses, timestamps, and authentication details.
• Helps identify the use of Tor or other anonymizing services during logins and transaction sessions, which is frequently associated with Darknet marketplace activity.

• Contains records of authentication events, user logins, and network activity, including timestamps, IP addresses, and session details.
• Assists in detecting anomalous successful voice-based authentication attempts or unusual logins that may reveal bypassed security checks due to deepfake impersonation.

Record user activities, authentication events, network traffic, and any attempts to bypass audit functions. Investigators analyze unauthorized balance adjustments or overridden logging mechanisms to identify digital tampering with financial records.

Captures user login activities, IP addresses, device IDs, and related metadata for e-commerce or payment apps. This data helps identify suspicious usage patterns, such as multiple transactions from the same IP or device under different accounts, revealing potentially coordinated manipulation.

Tracks user logins, account modifications, and system actions preceding early superannuation withdrawal filings. Alerts investigators to unauthorized activity or rapid account changes consistent with fraudulent or stolen identity claims.

Tracks user access events, including logins, timestamps, and IP addresses. By correlating expense report modifications with these logs, investigators can detect suspicious after-hours edits, backdating attempts, or repeated modification patterns that indicate intentional fraud.

• Captures detailed user and system activities, including IP addresses, login timestamps, and authentication events.
• Helps identify suspicious account creation patterns, such as multiple new accounts from the same device or location, and the repeated use of compromised credentials tied to fake or stolen identities.

• Record IP addresses, device identifiers, and login timestamps, highlighting geographic or device inconsistencies with the claimed identity.
• Provide audit trails to investigate unauthorized sessions and potential misuse of stolen or fabricated credentials.

Records device and network usage data, including login IP addresses, timestamps, and session activities. Conflicts between declared residence and consistent foreign IP origins can reveal misrepresented location details indicative of identity manipulation.

• Captures user login events, IP addresses, device fingerprints, and related session data within gaming platforms.
• Helps identify clusters of interlinked player accounts, item transfer patterns, and minimal legitimate game activity despite large in-game transactions.

• Records IP addresses, user authentication events, and device usage within gambling platforms.
• Correlates multiple gambling accounts linked by common IPs or devices, helping detect collusive behavior or funneling of funds to a single account.
• Supports investigations into suspicious transactions and staff involvement by providing audit trails of account access and administrative actions.

Captures detailed traces of user activities, system configurations, and monitoring rule changes. This data helps uncover unauthorized tampering with AML software or the disabling of compliance alerts by insiders, a hallmark tactic when criminals infiltrate a financial institution to suppress detection.

• Track user activity in banking and AML systems, including authentication events, access privileges, override submissions, and data modifications.
• Reveal patterns of employees disabling alerts, bypassing controls, or making suspicious system changes consistent with insider facilitation.

• Tracks IP addresses, device details, login timestamps, and possible use of anonymizing tools (e.g., VPNs).
• Detects unusual access patterns, suggesting attempts to conceal user location or identity on instant exchange platforms.

Captures staff logins, system changes, overrides of transactions or betting records, and any irregular use of internal systems. Such logs help detect unauthorized tampering or selective bypassing of AML checks for high-value players, indicating potential collusion or malicious insider activity in betting shops.

• Captures IP addresses, timestamps, and user authentication details for account creation and trading platform access.
• Identifies multiple new accounts associated with the same IP or location, suggesting coordinated manipulative trading.
• Provides audit trails useful in correlating suspicious trading patterns with specific network access events.

• Capture detailed records of user logins, access times, and system alterations.
• Reveal unauthorized updates to government financial systems or records, supporting the detection of tampering or falsified entries that mask stolen funds.

Centralized logs capture user actions and system activity, including edits to transaction details or supporting documentation. These logs help detect unauthorized changes to transaction purposes after scrutiny.

• Captures IP addresses, authentication events, and timestamps for user logins and web traffic.
• Allows detection of repeated access attempts from Tor exit nodes or known VPN servers.
• Enables investigators to correlate anomalous login locations with potential use of anonymous networking techniques, supporting timely identification of Onion over VPN usage.

• Records IP addresses, device information, session timestamps, and login attempts.
• Identifies logins or transaction instructions originating from IPs linked to known scam call centers or high-risk jurisdictions.
• Supports investigative efforts by mapping suspicious access patterns to pig butchering scam networks.

• Logs user authentication, IP addresses, session details, and potential anonymity software usage (e.g., Tor).
• Identifies suspicious network activity consistent with dark web access used to procure precursor chemicals or equipment.
• Correlates unusual access patterns with financial transaction events.

• Collects session data, including IP addresses, user-agent strings, timestamps, and authentication events.
• Enables correlation of these IPs with known proxy networks, Tor exit nodes, or suspicious short-term hosting services.
• Facilitates detection of frequent or abrupt IP address changes that indicate possible rotating proxy usage.
• Supports investigation by providing a clear audit trail of user sessions and highlighting anomalous network access patterns.

• Includes IP addresses, device identifiers, timestamps, and user session records tied to account logins.
• Helps detect multiple supposedly different accounts operated from the same endpoint or device, indicating potential mule networks or account takeovers.

Captures detailed user session data, including instances of remote desktop or screen-sharing software used during onboarding. This helps to uncover hidden user environments or bypassed identity verification protocols in remote account setups.

• Tracks the usage of remote control or screen-sharing tools during the verification process.
• Logs user and system activities (e.g., IP addresses, timestamps, application launches) to identify potential third-party manipulation of the verification interface.
• Helps uncover suspicious remote sessions that may subvert legitimate biometric or ID checks.

Captures IP addresses, device identifiers, and login timestamps. This data aids smurfing investigations by:

• Identifying multiple accounts accessed from the same device or IP, signaling potential collusion or single-user control of several smurf accounts.
• Pinpointing suspicious login patterns that correlate with bursts of small deposits in different accounts.

• Tracks user logins, session activities, IP addresses, and record modification events.
• Helps pinpoint unauthorized or off-hours access corresponding to suspected alterations in financial records.

• Provides user login records, including IP addresses, timestamps, device information, and geolocation data.
• Enables identification of known VPN or proxy endpoints and detection of sudden, improbable location changes.
• Facilitates investigation by correlating unusual login patterns with potential layering or obfuscation attempts.

Collects user login details, IP addresses, session timestamps, and device information. It aids in detecting frequently changing IPs, multiple concurrent connections, or cross-region logins—patterns often associated with layered laundering activities in virtual worlds.

• Captures IP addresses, device identifiers, login timestamps, and network session data.
• Reveals patterns of multiple trading accounts or wallets being accessed from the same devices or locations, indicating potential self-dealing.
• Enhances investigations by corroborating evidence of collusion through shared system access points.