ABUSE MAILBOX FOR FACILITATING DISCOVERY, INVESTIGATION, AND ANALYSIS OF EMAIL-BASED THREATS
A connection is established with a cloud-based email environment of an enterprise. A logical ingestion queue configured to receive user-generated reports of suspicious emails is monitored. A submission in the logical ingestion queue is detected, the submission comprising a first email reported by a first user. The first email is parsed to extract a plurality of header and content attributes. The first email is analyzed using a machine learning model to determine a threat classification indicating a probability that the first email is malicious. In response to the threat classification satisfying a risk threshold, a campaign signature is generated based on a subset of the plurality of header attributes or content attributes. The cloud-based email environment is queried using the campaign signature to identify a cluster of second emails delivered to a plurality of second users. The second emails exhibit similarity to the first email based on the campaign signature.
1 . A method comprising:
establishing a connection, via an application programming interface (API), with a cloud-based email environment of an enterprise;
monitoring a logical ingestion queue configured to receive user-generated reports of suspicious emails;
detecting a submission in the logical ingestion queue, the submission comprising a first email reported by a first user;
parsing the first email to extract a plurality of header attributes and content attributes;
analyzing the first email using a machine learning model to determine a threat classification indicating a probability that the first email is malicious;
in response to the threat classification satisfying a risk threshold, generating a campaign signature based on a subset of the plurality of header attributes or content attributes;
querying the cloud-based email environment, via the API, using the campaign signature to identify a cluster of second emails delivered to a plurality of second users, wherein the second emails exhibit similarity to the first email based on the campaign signature; and
automatically executing a remediation action on the cluster of second emails within the cloud-based email environment to prevent access to the second emails by the plurality of second users.
2 . The method of claim 1 , wherein the campaign signature comprises a similarity hash or fuzzy fingerprint generated from a body content of the first email, and wherein identifying the cluster of second emails comprises identifying emails having a similarity hash matching the campaign signature within a defined tolerance.
3 . The method of claim 1 , wherein the submission comprises a reporting message addressed to an abuse mailbox address, and wherein detecting the submission comprises extracting the first email as an attachment from the reporting message.
4 . The method of claim 1 , wherein generating the campaign signature comprises calculating a deterministic grouping identifier based on a combination of a sender address, a subject line, and a body content hash of the first email.
5 . The method of claim 1 , further comprising: updating a federated threat database with the campaign signature, wherein the federated threat database is accessible to a plurality of distinct enterprises; and blocking delivery of inbound emails matching the campaign signature for the plurality of distinct enterprises based on the threat classification of the first email.
6 . The method of claim 1 , wherein the remediation action comprises modifying at least a portion of the second emails to disable selectable hyperlinks contained therein or inserting a warning banner into at least a portion of the second emails.
7 . The method of claim 1 , further comprising: generating a notification data packet indicating that the remediation action has been executed on the cluster of second emails; and transmitting the notification data packet to a registered administrator device via a plurality of parallel communication channels comprising at least two of: a short message service (SMS) gateway, a push notification service associated with a mobile application, or a simple mail transfer protocol (SMTP) relay, wherein the transmitting is performed synchronously with the automatically executing of the remediation action to minimize a time-to-awareness latency.
8 . The method of claim 1 , further comprising: receiving a restoration command designated for the first email; and in response to the restoration command, automatically triggering a batch restoration process via the API, the batch restoration process comprising identifying a current storage location of each of the second emails in the cluster and moving each of the second emails from the current storage location back to a respective primary inbox of each of the plurality of second users.
9 . The method of claim 1 , wherein the automatically executing the remediation action is gated by a tenant-specific configuration setting defining an operational mode, and wherein the method further comprises: determining that the tenant-specific configuration setting is set to a passive mode; in response to the determining, inhibiting the remediation action; and generating a shadow remediation log entry accessible via a dashboard, the shadow remediation log entry presenting the cluster of second emails and the campaign signature as if the remediation action had been executed.
10 . The method of claim 1 , wherein the first email comprises an internal communication originating from a sender account associated with the enterprise, the method further comprising: correlating the threat classification with sign-in telemetry associated with the sender account to determine a probability of account compromise; and in response to the probability satisfying a compromise threshold, automatically executing an identity remediation workflow via the API, the identity remediation workflow comprising transmitting a command to an identity provider to revoke an active session token for the sender account and trigger a mandatory password reset on a next login attempt.
11 . The method of claim 1 , wherein analyzing the first email comprises extracting a uniform resource locator (URL) identified as a credential harvesting link, and wherein the method further comprises: querying an audit log of the cloud-based email environment via the API to identify a subset of the plurality of second users who actuated the URL prior to the automatically executing of the remediation action; and designating the subset of second users as high-risk entities and automatically initiating a re-authentication challenge for each user in the subset via an integrated multi-factor authentication (MFA) service.
12 . The method of claim 1 , further comprising: retrieving, via the API, directory attributes for a sender of the first email and the first user, the directory attributes defining an organizational hierarchy; calculating a social graph distance between the sender and the first user; and modifying the risk threshold based on the social graph distance and the directory attributes, such that a communication anomaly between distant nodes in the organizational hierarchy is weighted with a higher probability of being malicious compared to a communication anomaly between proximate nodes.
13 . The method of claim 1 , wherein monitoring the logical ingestion queue comprises: configuring an API endpoint to receive external threat alerts from a third-party security gateway; normalizing the external threat alerts into a standardized submission format compatible with the user-generated reports; and injecting the normalized alerts into the logical ingestion queue, such that the third-party security gateway functions as a virtual reporting user to trigger the analyzing, generating of the campaign signature, and automatically executing of the remediation action.
14 . The method of claim 1 , further comprising: generating a confirmed threat dataset comprising the first email and the threat classification, validated by the executing of the remediation action; initiating a retraining process for the machine learning model using the confirmed threat dataset to update a set of model weights; and versioning the machine learning model to create a tenant-specific model instance that is distinct from a global base model, wherein the tenant-specific model instance is prioritized for analyzing subsequent submissions from the enterprise.
15 . The method of claim 1 , wherein generating the campaign signature comprises applying a locality-sensitive hashing (LSH) algorithm to the content attributes to produce an anonymized feature vector, and wherein the method further comprises: publishing the anonymized feature vector to a distributed ledger or federated database accessible by a plurality of distinct tenant environments; and enabling a subscribing tenant environment to query the federated database to preemptively identify and block inbound emails matching the anonymized feature vector before a local user report is generated in the subscribing tenant environment.
16 . The method of claim 1 , wherein querying the cloud-based email environment comprises: defining a temporal search window anchored to a receipt timestamp of the first email; retrieving message metadata for emails received by the plurality of second users only within the temporal search window; and applying a density-based clustering algorithm to the retrieved message metadata to identify the cluster of second emails.
17 . The method of claim 1 , further comprising: rendering a campaign visualization interface on a display device, the interface comprising a timeline view of the cluster of second emails and a threat breakdown by recipient department; displaying a dynamic status indicator for each of the second emails, the status indicator updating in real-time to reflect a state change from delivered to remediated; and providing a single-actuation control element within the interface configured to, upon activation, transmit a bulk API command to modify the remediation action for the entire cluster of second emails simultaneously.
18 . The method of claim 1 , wherein the remediation action comprises a sanitization workflow comprising: downloading the second emails from the cloud-based email environment to a secure sandbox environment; parsing a document object model (DOM) of a body of the second emails to identify and neutralize active content components comprising scripts or selectable hyperlinks, while preserving static text content; and uploading the neutralized second emails back to the cloud-based email environment to replace the original second emails.
19 . A system, comprising:
a processor configured to:
establish a connection, via an application programming interface (API), with a cloud-based email environment of an enterprise;
monitor a logical ingestion queue configured to receive user-generated reports of suspicious emails;
detect a submission in the logical ingestion queue, the submission comprising a first email reported by a first user;
parse the first email to extract a plurality of header attributes and content attributes;
analyze the first email using a machine learning model to determine a threat classification indicating a probability that the first email is malicious;
in response to the threat classification satisfying a risk threshold, generate a campaign signature based on a subset of the plurality of header attributes or content attributes;
query the cloud-based email environment, via the API, using the campaign signature to identify a cluster of second emails delivered to a plurality of second users, wherein the second emails exhibit similarity to the first email based on the campaign signature; and
automatically execute a remediation action on the cluster of second emails within the cloud-based email environment to prevent access to the second emails by the plurality of second users; and
a memory coupled to the processor and configured to provide the processor with instructions.
20 . A computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for:
establishing a connection, via an application programming interface (API), with a cloud-based email environment of an enterprise;
monitoring a logical ingestion queue configured to receive user-generated reports of suspicious emails;
detecting a submission in the logical ingestion queue, the submission comprising a first email reported by a first user;
parsing the first email to extract a plurality of header attributes and content attributes;
analyzing the first email using a machine learning model to determine a threat classification indicating a probability that the first email is malicious;
in response to the threat classification satisfying a risk threshold, generating a campaign signature based on a subset of the plurality of header attributes or content attributes;
querying the cloud-based email environment, via the API, using the campaign signature to identify a cluster of second emails delivered to a plurality of second users, wherein the second emails exhibit similarity to the first email based on the campaign signature; and
automatically executing a remediation action on the cluster of second emails within the cloud-based email environment to prevent access to the second emails by the plurality of second users.