The periodic audit of Synapse activity is intended to surface potential threat scenarios concerning the privacy and security of data held in the Synapse. The approach to this audit is informed by an assessment of risks to priority data, such as the data sets associated with Synapse projects marked with restricted access control lists. The risk assessment process considers access control at the point when access is granted, when access is used, and when access may become uncontrolled.
Auditing may be done by analyzing a representative sample of activity or a comprehensive report of activity over the audit period. A comprehensive report is preferred when the queries driving the report can be targeted to precisely address the threat scenario. Sampling is used as an alternative when comprehensive reporting is not feasible to address a given audit query, such as for activity common to all users within the application.
Threat Scenarios
Data access
Synapse implements an access control system based on the properties of the profile attempting to access information and on properties of the data set itself. An account must be validated in order to access controlled use data, and an access restriction must be in place on data with a controlled use classification in order to implement this access control.
Threat: A Synapse user intentionally or inadvertently accesses controlled data without qualification of their account
Identify through data warehouse query and end user reporting:
Users who have posted or access controlled data without the the appropriate validation property on their account.
Users who should have access removed at a prior time no longer have access
Threat: A Synapse user with significant access to data intentionally or inadvertently shares access
Identify through data warehouse query and end user reporting:
A single file downloaded multiple times by a single user
Associated queries: MD5 duplicates, Restriction change of state, Top downloaders
Data handling
Synapse allows end users to upload data once they have certified their account through a training module. The certification process is an administrative control that trains users on appropriate data handling procedures. Once granted data upload rights, an end user is expected to respect the permission sets associated with the data sets they handle.
Threat: A Synapse superuser intentionally or accidentally copies or uploads a controlled data set without appropriate access controls
Identify through data warehouse query and end user reporting:
PHI accidentally/intentionally released without appropriate conditions
Original terms of data contribution are not respected. Data proliferated into Synapse beyond the original terms of use
Public Synapse spaces contain only data classified as public
Associated queries: MD5 duplicates, Restriction change of state
Data loss
A Synapse account may be permitted to access many data sets of differing classifications. An incident of account sharing or account compromise may result in the download of a data set beyond what is intended according to an access restriction.
Threat: A Synapse account with extensive access to controlled data sets may be compromised:
Identify through data warehouse query and end user reporting:
Detecting the exfiltration of data from Synapse correlated with large-scale download activity by a user
Associated queries: Restriction change of state, Top downloaders
Audit Constraints
The Synapse audit approach was revised in 2020 to focus on specific threats identified through a risk assessment process. Automated queries were designed to report on the activity related to each threat.
The audit reports are limited by the time spans available to the automated queries. Some queries are based on changes to properties of objects and a query may not be able to compare an event with activity outside of its observation window. In these cases, the query will not surface a conflict between the event and a prior state.
Data warehouse queries
Restriction change of state
#select t1.ID, t1.IS_CONTROLLED, t1.IS_RESTRICTED, t1.IS_PUBLIC, t2.IS_CONTROLLED, t2.IS_RESTRICTED, t2.IS_PUBLIC
select t1.*, t2.*
from (
select ns2.*
from NODE_SNAPSHOT ns2
join (
# most recent snapshot
select ns1.ID, max(ns1.TIMESTAMP)
from NODE_SNAPSHOT ns1
group by ns1.ID
) nsmax1 on nsmax1.ID=ns2.ID
) t1
join (
select ns2.*
from NODE_SNAPSHOT ns2
join (
# snapshot a month ago
select ns1.ID, max(ns1.TIMESTAMP)
from NODE_SNAPSHOT ns1
where ns1.TIMESTAMP < unix_timestamp('2019-09-01 00:00:00')*1000
group by ns1.ID
) nsmax1 on nsmax1.ID=ns2.ID
) t2 on t2.ID=t1.ID and t2.VERSION_NUMBER=t1.VERSION_NUMBER
where not (t1.IS_PUBLIC = t2.IS_PUBLIC and t1.IS_CONTROLLED = t2.IS_CONTROLLED and t1.IS_RESTRICTED = t2.IS_RESTRICTED)
limit 100
;
Top downloaders
# top 20 downloaders by count(filehandle_id)
select fhdr.USER_ID, count(*) as c
from FILE_HANDLE_DOWNLOAD_RECORD fhdr
where fhdr.TIMESTAMP between unix_timestamp('2019-07-01 00:00:00')*1000 and unix_timestamp('2019-09-10 00:00:00')*1000
group by fhdr.USER_ID
order by c desc
limit 20;