Comments (9)
Could you try again? Do you have both ipv4 and ipv6 data? What version of the app do you use?
from suspicious_login.
Nextcloud 16.0.5
Suspicious Login 1.0.0
IPv4 only
Still the same result: Not enough data, try again later (Insufficient data: No recent data available)
from suspicious_login.
That is strange. Could you run an SQL query to count the number of rows in oc_login_address_aggregated
that have a first_seen
larger than the unix timestamp from a week ago?
The only case where you might not have new IPs for the last week is when your IPs never change. But that seems unlikely.
from suspicious_login.
MariaDB [nextcloud]> SELECT id,seen,
-> DATE_FORMAT(FROM_UNIXTIME(first_seen),'%Y-%m-%dT%TZ') as first_seen,
-> DATE_FORMAT(FROM_UNIXTIME(last_seen),'%Y-%m-%dT%TZ') as last_seen
-> FROM oc_login_address_aggregated
-> WHERE first_seen>DATE_SUB(NOW(), INTERVAL 1 WEEK);
Empty set, 44 warnings (0.00 sec)
I don't know what the records in this table mean. However, I did logout/login in a web browser, and restarted the client on a machine, without any modification in this table (neither the last_seen column).
FYI, I use TOTP on my own, but I also have a Synology that syncs in webdav. One of my colleague also syncs his Synology, but not sure he use the client. Users are also authed in LDAP (Active Directory).
If you have a doubt on my request, here is the content of the table:
MariaDB [nextcloud]> SELECT id,seen,
-> DATE_FORMAT(FROM_UNIXTIME(first_seen),'%Y-%m-%dT%TZ') as first_seen,
-> DATE_FORMAT(FROM_UNIXTIME(last_seen),'%Y-%m-%dT%TZ') as last_seen
-> FROM oc_login_address_aggregated;
+----------+----------+----------------------+----------------------+
| id | seen | first_seen | last_seen |
+----------+----------+----------------------+----------------------+
| 1 | 29307778 | 2019-06-04T22:34:36Z | 2019-10-09T06:41:36Z |
| 648 | 30123 | 2019-06-04T22:37:11Z | 2019-10-09T02:55:32Z |
| 215970 | 18 | 2019-06-05T15:43:41Z | 2019-09-27T15:13:51Z |
| 461456 | 3 | 2019-06-06T12:37:05Z | 2019-06-06T13:38:26Z |
| 564536 | 4 | 2019-06-07T21:49:51Z | 2019-06-07T21:57:41Z |
| 1537240 | 4 | 2019-06-11T11:59:12Z | 2019-06-11T11:59:13Z |
| 2160305 | 4 | 2019-06-14T09:52:23Z | 2019-06-14T10:40:49Z |
| 4678419 | 10 | 2019-06-23T19:45:52Z | 2019-06-25T19:41:16Z |
| 4884910 | 532 | 2019-06-24T10:17:24Z | 2019-10-08T08:59:55Z |
| 6286938 | 22 | 2019-06-28T14:21:34Z | 2019-07-06T13:25:16Z |
| 6664333 | 1317 | 2019-06-29T17:52:47Z | 2019-06-29T19:29:01Z |
| 6932598 | 26 | 2019-06-30T12:06:36Z | 2019-06-30T12:06:55Z |
| 8461734 | 104 | 2019-07-12T10:14:57Z | 2019-10-07T19:57:56Z |
| 9462170 | 2 | 2019-07-15T15:37:51Z | 2019-07-15T15:37:51Z |
| 9491559 | 2 | 2019-07-30T16:57:41Z | 2019-07-30T16:57:41Z |
| 9865499 | 2 | 2019-07-31T17:33:21Z | 2019-07-31T17:33:21Z |
| 12189113 | 3 | 2019-08-07T16:30:22Z | 2019-09-03T11:16:40Z |
| 12433925 | 4 | 2019-08-08T09:38:24Z | 2019-09-03T15:31:29Z |
| 13613275 | 2 | 2019-08-12T10:10:24Z | 2019-08-12T10:10:24Z |
| 13982567 | 3 | 2019-08-13T10:14:15Z | 2019-08-13T15:43:00Z |
| 14338698 | 3 | 2019-08-14T10:04:00Z | 2019-09-05T19:11:05Z |
| 14446679 | 2 | 2019-08-14T22:08:39Z | 2019-08-14T22:08:39Z |
| 14491331 | 2 | 2019-08-18T18:51:33Z | 2019-08-18T18:51:33Z |
| 14775786 | 2 | 2019-08-19T17:08:13Z | 2019-08-19T17:08:13Z |
| 15064891 | 3 | 2019-08-20T13:36:23Z | 2019-08-20T13:43:03Z |
| 15105664 | 6 | 2019-08-20T16:16:07Z | 2019-08-26T17:42:29Z |
| 17149344 | 2 | 2019-08-26T11:37:13Z | 2019-08-26T11:37:13Z |
| 17244033 | 2 | 2019-08-26T17:50:48Z | 2019-08-26T17:50:48Z |
| 18222581 | 7 | 2019-08-29T13:04:13Z | 2019-09-23T10:13:30Z |
| 19597374 | 2 | 2019-09-02T10:14:29Z | 2019-09-02T10:14:29Z |
| 19996955 | 4 | 2019-09-06T09:05:14Z | 2019-09-10T08:24:08Z |
| 20025304 | 79 | 2019-09-06T15:17:35Z | 2019-10-09T03:28:32Z |
| 20057593 | 2 | 2019-09-06T22:13:21Z | 2019-09-06T22:13:21Z |
| 20561952 | 3 | 2019-09-12T13:20:51Z | 2019-09-13T12:54:36Z |
| 20659650 | 3 | 2019-09-13T10:53:53Z | 2019-09-13T11:02:03Z |
| 21006513 | 2 | 2019-09-16T14:00:32Z | 2019-09-16T14:00:32Z |
| 21118706 | 5 | 2019-09-17T13:34:24Z | 2019-09-18T13:55:06Z |
| 22025968 | 2 | 2019-09-25T13:52:14Z | 2019-09-25T13:52:14Z |
| 22028864 | 2 | 2019-09-25T14:31:02Z | 2019-09-25T14:31:02Z |
| 22129515 | 2 | 2019-09-26T14:26:17Z | 2019-09-26T14:26:17Z |
| 22190039 | 5 | 2019-09-27T07:34:53Z | 2019-09-27T23:42:03Z |
| 22203054 | 2 | 2019-09-27T10:43:51Z | 2019-09-27T10:43:51Z |
| 22571308 | 2 | 2019-10-01T14:33:50Z | 2019-10-01T14:33:50Z |
| 22596178 | 2 | 2019-10-01T22:13:25Z | 2019-10-01T22:13:25Z |
+----------+----------+----------------------+----------------------+
44 rows in set (0.00 sec)
from suspicious_login.
I don't know what the records in this table mean. However, I did logout/login in a web browser, and restarted the client on a machine, without any modification in this table (neither the last_seen column).
The login data is not directly fed into that table. It first goes into oc_login_address
and a background job updates the oc_login_address_aggregated
asynchronously.
If you have a doubt on my request, here is the content of the table:
That is indeed strange. Do you use some sort of proxy in front of Nextcloud? Does Nextcloud even see the client IPs?
from suspicious_login.
I don't know what the records in this table mean
It's basically a compressed version of oc_login_address
, in which every login is stored as a row. The aggregated data uses a counter to groups identic (uid,ip) tupes. The timestamps show when a (uid,ip) was used first and last. In your case this compressed 30M entries into <50 rows ;)
from suspicious_login.
This instance of nextcloud is the only one I have without a reverse proxy. Instead, I have a NAT 1:1 configured in a pfsense (means that there is a dedicated IP address for this service, which is also used for outgoing traffic).
The 50 rows are not such a surprise. We are only few users, usually connecting from the same IP addresses.
from suspicious_login.
The problem here is: the current logic tries to split collected data into two sets: training data and validation data. Validation data is the IPs that have only been seen in the last week. The idea behind this is to give a metric of how well the model reacts to historically new data. If your IPs hardly ever change, there won't be anything new recently.
This is a conceptual problem. I'm not sure if this is solvable easily.
from suspicious_login.
So basically, your saying that the use of this app is irrelevant in case the instance is safe and only used by a few users?
What if there is one big attacker in these early stages of the nextcloud instance?
Honestly, I believe hackers have better to do than target ultra-small teams, so if this add-on is not useful in that particular case, I'd rather disable it to avoid Warnings in the log section.
It keeps telling me that the models are not present (Could not predict suspiciousness: No models found) or that there is not enough data.
from suspicious_login.
Related Issues (20)
- Replace lint.yml with split workflows
- Dependency Dashboard
- Update rubixML HOT 15
- App not passing integrity check in v26/25 HOT 3
- Too verbose logs when model not found HOT 1
- Unit tests don't execute against php 8.2
- Add button to email notifications to get more info about the suspicious ip HOT 1
- A new login into your account was detected - really a login, or just a try? HOT 1
- Drop support for PHP 7.4 HOT 2
- PHP unserialize(): Error at offset HOT 5
- 0 rows on login_address table HOT 1
- Version on app store and compatible versions HOT 1
- Investigate feasibility of use in 32-bit environments HOT 2
- Email Notification: New login location detected HOT 2
- Huge database table due to login attempts/reconnects from Thunderbird client CalDAV HOT 1
- Datasets must have the same number of columns HOT 11
- All logins reported as suspicious - underlying DataLoader.php bug HOT 1
- Can not start training HOT 1
- Suspicious Login notification whenever logged in (thousands of warnings) HOT 2
- ValueError during IPv4 background training HOT 1
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from suspicious_login.